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目录Part 1 PID type fuzzy controller and parameters adaptive method (1)Part 2 Application of self adaptation fuzzy-PID control for main steam temperature control system in power station (7)Part 3 Neuro-fuzzy generalized predictive control of boiler steam temperature ..................................................................... (13)Part 4 为Part3译文：锅炉蒸汽温度模糊神经网络的广义预测控制21Part 1 PID type fuzzy controller and Parametersadaptive methodWu zhi QIAO, Masaharu MizumotoAbstract: The authors of this paper try to analyze the dynamic behavior of the product-sum crisp type fuzzy controller, revealing that this type of fuzzy controller behaves approximately like a PD controller that may yield steady-state error for the control system. By relating to the conventional PID control theory, we propose a new fuzzy controller structure, namely PID type fuzzy controller which retains the characteristics similar to the conventional PID controller. In order to improve further the performance of the fuzzy controller, we work out a method to tune the parameters of the PID type fuzzy controller on line, producing a parameter adaptive fuzzy controller. Simulation experiments are made to demonstrate the fine performance of these novel fuzzy controller structures.Keywords: Fuzzy controller; PID control; Adaptive control1. IntroductionAmong various inference methods used in the fuzzy controller found in literatures , the most widely used ones in practice are the Mamdani method proposed by Mamdani and his associates who adopted the Min-max compositional rule of inference based on an interpretation of a control rule as a conjunction of the antecedent and consequent, and the product-sum method proposed by Mizumoto who suggested to introduce the product and arithmetic mean aggregation operators to replace the logical AND (minimum) and OR (maximum) calculations in the Min-max compositional rule of inference.In the algorithm of a fuzzy controller, the fuzzy function calculation is also a complicated and time consuming task. Tagagi and Sugeno proposed a crisp type model in which the consequent parts of the fuzzy control rules are crisp functional representation or crisp real numbers in the simplified case instead of fuzzy sets . With this model of crisp real number output, the fuzzy set of the inference consequence willbe a discrete fuzzy set with a finite number of points, this can greatly simplify the fuzzy function algorithm.Both the Min-max method and the product-sum method are often applied with the crisp output model in a mixed manner. Especially the mixed product-sum crisp model has a fine performance and the simplest algorithm that is very easy to be implemented in hardware system and converted into a fuzzy neural network model. In this paper, we will take account of the product-sum crisp type fuzzy controller.2. PID type fuzzy controller structureAs illustrated in previous sections, the PD function approximately behaves like a parameter time-varying PD controller. Since the mathematical models of most industrial process systems are of type, obviously there would exist an steady-state error if they are controlled by this kind of fuzzy controller. This characteristic has been stated in the brief review of the PID controller in the previous section.If we want to eliminate the steady-state error of the control system, we can imagine to substitute the input (the change rate of error or the derivative of error) of the fuzzy controller with the integration of error. This will result the fuzzy controller behaving like a parameter time-varying PI controller, thus the steady-state error is expelled by the integration action. However, a PI type fuzzy controller will have a slow rise time if the P parameters are chosen small, and have a large overshoot if the P or I parameters are chosen large. So there may be the time when one wants to introduce not only the integration control but the derivative control to the fuzzy control system, because the derivative control can reduce the overshoot of the system's response so as to improve the control performance. Of course this can be realized by designing a fuzzy controller with three inputs, error, the change rate of error and the integration of error. However, these methods will be hard to implement in practice because of the difficulty in constructing fuzzy control rules. Usually fuzzy control rules are constructed by summarizing the manual control experience of an operator who has been controlling the industrial process skillfully and successfully. The operator intuitively regulates the executor to control the process by watching theerror and the change rate of the error between the system's output and the set-point value. It is not the practice for the operator to observe the integration of error. Moreover, adding one input variable will greatly increase the number of control rules, the constructing of fuzzy control rules are even more difficult task and it needs more computation efforts. Hence we may want to design a fuzzy controller that possesses the fine characteristics of the PID controller by using only the error and the change rate of error as its inputs.One way is to have an integrator serially connected to the output of the fuzzy controller as shown in Fig. 1. In Fig. 1,1K and 2K are scaling factors for e and ~ respectively, and fl is the integral constant. In the proceeding text, for convenience, we did not consider the scaling factors. Here in Fig. 2, when we look at the neighborhood of NODE point in the e - ~ plane, it follows from (1) that the control input to the plant can be approximated by(1)Hence the fuzzy controller becomes a parameter time-varying PI controller, itsequivalent proportional control and integral control components are BK2D and ilK1 P respectively. We call this fuzzy controller as the PI type fuzzy controller (PI fc). We can hope that in a PI type fuzzy control system, the steady-state error becomes zero.To verify the property of the PI type fuzzy controller, we carry out some simulation experiments. Before presenting the simulation, we give a description of the simulation model. In the fuzzy control system shown in Fig. 3, the plant model is a second-order and type system with the following transfer function:)1)(1()(21++=s T s T K s G (2) Where K = 16, 1T = 1, and 2T = 0.5. In our simulation experiments, we use thediscrete simulation method, the results would be slightly different from that of a continuous system, the sampling time of the system is set to be 0.1 s. For the fuzzy controller, the fuzzy subsets of e and d are defined as shown in Fig. 4. Their coresThe fuzzy control rules are represented as Table 1. Fig. 5 demonstrates the simulation result of step response of the fuzzy control system with a Pl fc. We can see that the steady-state error of the control system becomes zero, but when the integration factor fl is small, the system's response is slow, and when it is too large, there is a high overshoot and serious oscillation. Therefore, we may want to introduce the derivative control law into the fuzzy controller to overcome the overshoot and instability. We propose a controller structure that simply connects the PD type and the PI type fuzzy controller together in parallel. We have the equivalent structure of that by connecting a PI device with the basic fuzzy controller serially as shown in Fig.6. Where ~ is the weight on PD type fuzzy controller and fi is that on PI type fuzzy controller, the larger a/fi means more emphasis on the derivative control and less emphasis on the integration control, and vice versa. It follows from (7) that the output of the fuzzy controller is(3)3. The parameter adaptive methodThus the fuzzy controller behaves like a time-varying PID controller, its equivalent proportional control, integral control and derivative control components are respectively. We call this new controller structure a PID type fuzzy controller (PID fc). Figs. 7 and 8 are the simulation results of the system's step response of such control system. The influence of ~ and fl to the system performance is illustrated. When ~ > 0 and/3 = 0, meaning that the fuzzy controller behaves like PD fc, there exist a steady-state error. When ~ = 0 and fl > 0, meaning that the fuzzy controller behaves like a PI fc, the steady-state error of the system is eliminated but there is a large overshoot and serious oscillation.When ~ > 0 and 13 > 0 the fuzzy controller becomes a PID fc, the overshoot is substantially reduced. It is possible to get a comparatively good performance by carefully choosing the value of αandβ.4. ConclusionsWe have studied the input-output behavior of the product-sum crisp type fuzzy controller, revealing that this type of fuzzy controller behaves approximately like a parameter time-varying PD controller. Therefore, the analysis and designing of a fuzzy control system can take advantage of the conventional PID control theory. According to the coventional PID control theory, we have been able to propose some improvement methods for the crisp type fuzzy controller.It has been illustrated that the PD type fuzzy controller yields a steady-state error for the type system, the PI type fuzzy controller can eliminate the steady-state error. We proposed a controller structure, that combines the features of both PD type and PI type fuzzy controller, obtaining a PID type fuzzy controller which allows the control system to have a fast rise and a small overshoot as well as a short settling time.To improve further the performance of the proposed PID type fuzzy controller, the authors designed a parameter adaptive fuzzy controller. The PID type fuzzy controller can be decomposed into the equivalent proportional control, integral control and the derivative control components. The proposed parameter adaptive fuzzy controller decreases the equivalent integral control component of the fuzzy controller gradually with the system response process time, so as to increase the damping of the system when the system is about to settle down, meanwhile keeps the proportional control component unchanged so as to guarantee quick reaction against the system's error. With the parameter adaptive fuzzy controller, the oscillation of the system is strongly restrained and the settling time is shortened considerably.We have presented the simulation results to demonstrate the fine performance of the proposed PID type fuzzy controller and the parameter adaptive fuzzy controller structure.Part 2 Application of self adaptation fuzzy-PID control for main steam temperature control system inpower stationZHI-BIN LIAbstract: In light of the large delay, strong inertia, and uncertainty characteristics of main steam temperature process, a self adaptation fuzzy-PID serial control system is presented, which not only contains the anti-disturbance performance of serial control, but also combines the good dynamic performance of fuzzy control. The simulation results show that this control system has more quickly response, better precision and stronger anti-disturbance ability．Keywords：Main steam temperature；Self adaptation；Fuzzy control；Serial control1. IntroductionThe boiler superheaters of modem thermal power station run under the condition of high temperature and high pressure, and the superheater’s temperature is highest in the steam channels．so it has important effect to the running of the whole thermal power station．If the temperature is too high, it will be probably burnt out. If the temperature is too low ,the efficiency will be reduced So the main steam temperature mast be strictly controlled near the given value．Fig l shows the boiler main steam temperature system structure.Fig.1 boiler main steam temperature systemIt can be concluded from Fig l that a good main steam temperature controlsystem not only has adequately quickly response to flue disturbance and load fluctuation, but also has strong control ability to desuperheating water disturbance. The general control scheme is serial PID control or double loop control system with derivative. But when the work condition and external disturbance change large, the performance will become instable. This paper presents a self adaptation fuzzy-PID serial control system. which not only contains the anti-disturbance performance of serial control, but also combines the good dynamic character and quickly response of fuzzy control ．1. Design of Control SystemThe general regulation adopts serial PID control system with load feed forward ．which assures that the main steam temperature is near the given value 540℃in most condition ．If parameter of PID control changeless and the work condition and external disturbance change large, the performance will become in stable ．The fuzzy control is fit for controlling non-linear and uncertain process. The general fuzzy controller takes error E and error change ratio EC as input variables ．actually it is a non-linear PD controller, so it has the good dynamic performance ．But the steady error is still in existence. In linear system theory, integral can eliminate the steady error. So if fuzzy control is combined with PI control, not only contains the anti-disturbance performance of serial control, but also has the good dynamic performance and quickly response.In order to improve fuzzy control self adaptation ability, Prof ．Long Sheng-Zhao and Wang Pei-zhuang take the located in bringing forward a new idea which can modify the control regulation online ．This regulation is:]1,0[,)1(∈-+=αααEC E UThis control regulation depends on only one parameter α.Once αis fixed ．the weight of E and EC will be fixed and the self adaptation ability will be very small ．It was improved by Prof. Li Dong-hui and the new regulation is as follow;]1,0[,,,3,)1(2,)1(1,)1(0,)1({321033221100∈±=-+±=-+±=-+=-+=ααααααααααααE EC E E EC E E EC E E EC E UBecause it is very difficult to find a self of optimum parameter, a new method is presented by Prof ．Zhou Xian-Lan, the regulation is as follow:)0(),ex p(12>--=k ke αBut this algorithm still can not eliminate the steady error ．This paper combines this algorithm with PI control ，the performance is improved ．2. Simulation of Control System3.1 Dynamic character of controlled objectPapers should be limited to 6 pages Papers longer than 6 pages will be subject to extra fees based on their length ．Fig .2 main steam temperature control system structureFig 2 shows the main steam temperature control system structure ，)(),(21s W s W δδare main controller and auxiliary controller,)(),(21s W s W o o are characters of the leading and inertia sections,)(),(21s W s W H H are measure unit.3.2 Simulation of the general serial PID control systemThe simulation of the general serial PID control system is operated by MATLAB, the simulation modal is as Fig.3.Setp1 and Setp2 are the given value disturbance and superheating water disturb & rice .PID Controller1 and PID Controller2 are main controller and auxiliary controller ．The parameter value which comes from references is as follow ：667.37,074.0,33.31)(25)(111111122===++===D I p D I p p k k k s k sk k s W k s W δδFig.3. the general PID control system simulation modal3.3 Simulation of self adaptation fuzzy-PID control system SpacingThe simulation modal is as Fig 4.Auxiliary controller is:25)(22==p k s W δ.Main controller is Fuzzy-PI structure, and the PI controller is:074.0,33.31)(11111==+=I p I p k k s k k s W δFuzzy controller is realized by S-function, and the code is as fig.5.Fig.4. the fuzzy PID control system simulation modalFig 5 the S-function code of fuzzy control3.4 Comparison of the simulationGiven the same given value disturbance and the superheating water disturbance，we compare the response of fuzzy-PID control system with PID serial control system. The simulation results are as fig.6-7.From Fig6-7,we can conclude that the self adaptation fuzzy-PID control system has the more quickly response, smaller excess and stronger anti-disturbance．4. Conclusion(1)Because it combines the advantage of PID controller and fuzzy controller, theself adaptation fuzzy-PID control system has better performance than the general PID serial control system.(2)The parameter can self adjust according to the error E value. so this kind of controller can harmonize quickly response with system stability．Part 3 Neuro-fuzzy generalized predictive controlof boiler steam temperatureXiangjie LIU, Jizhen LIU, Ping GUANAbstract: Power plants are nonlinear and uncertain complex systems. Reliable control of superheated steam temperature is necessary to ensure high efficiency and high load-following capability in the operation of modern power plant. A nonlinear generalized predictive controller based on neuro-fuzzy network (NFGPC) is proposed in this paper. The proposed nonlinear controller is applied to control the superheated steam temperature of a 200MW power plant. From the experiments on the plant and the simulation of the plant, much better performance than the traditional controller is obtained.Keywords: Neuro-fuzzy networks; Generalized predictive control; Superheated steam temperature1. IntroductionContinuous process in power plant and power station are complex systems characterized by nonlinearity, uncertainty and load disturbance. The superheater is an important part of the steam generation process in the boiler-turbine system, where steam is superheated before entering the turbine that drives the generator. Controlling superheated steam temperature is not only technically challenging, but also economically important.From Fig.1,the steam generated from the boiler drum passes through the low-temperature superheater before it enters the radiant-type platen superheater. Water is sprayed onto the steam to control the superheated steam temperature in both the low and high temperature superheaters. Proper control of the superheated steam temperature is extremely important to ensure the overall efficiency and safety of the power plant. It is undesirable that the steam temperature is too high, as it can damage the superheater and the high pressure turbine, or too low, as it will lower the efficiency of the power plant. It is also important to reduce the temperaturefluctuations inside the superheater, as it helps to minimize mechanical stress that causes micro-cracks in the unit, in order to prolong the life of the unit and to reduce maintenance costs. As the GPC is derived by minimizing these fluctuations, it is amongst the controllers that are most suitable for achieving this goal.The multivariable multi-step adaptive regulator has been applied to control the superheated steam temperature in a 150 t/h boiler, and generalized predictive control was proposed to control the steam temperature. A nonlinear long-range predictive controller based on neural networks is developed into control the main steam temperature and pressure, and the reheated steam temperature at several operating levels. The control of the main steam pressure and temperature based on a nonlinear model that consists of nonlinear static constants and linear dynamics is presented in that.Fig.1 The boiler and superheater steam generation process Fuzzy logic is capable of incorporating human experiences via the fuzzy rules. Nevertheless, the design of fuzzy logic controllers is somehow time consuming, as the fuzzy rules are often obtained by trials and errors. In contrast, neural networks not only have the ability to approximate non-linear functions with arbitrary accuracy, they can also be trained from experimental data. The neuro-fuzzy networks developed recently have the advantages of model transparency of fuzzy logic and learning capability of neural networks. The NFN is have been used to develop self-tuning control, and is therefore a useful tool for developing nonlinear predictive control. Since NFN is can be considered as a network that consists of several local re-gions, each of which contains a local linear model, nonlinear predictive control based onNFN can be devised with the network incorporating all the local generalized predictive controllers (GPC) designed using the respective local linear models. Following this approach, the nonlinear generalized predictive controllers based on the NFN, or simply, the neuro-fuzzy generalized predictive controllers (NFG-PCs)are derived here. The proposed controller is then applied to control the superheated steam temperature of the 200MW power unit. Experimental data obtained from the plant are used to train the NFN model, and from which local GPC that form part of the NFGPC is then designed. The proposed controller is tested first on the simulation of the process, before applying it to control the power plant.2. Neuro-fuzzy network modellingConsider the following general single-input single-output nonlinear dynamic system:),1(),...,(),(),...,1([)(''+-----=uy n d t u d t u n t y t y f t y ∆+--/)()](),...,1('t e n t e t e e (1)where f[.]is a smooth nonlinear function such that a Taylor series expansion exists, e(t)is a zero mean white noise and Δis the differencing operator,''',,e u y n n n and d are respectively the known orders and time delay of the system. Let the local linear model of the nonlinear system (1) at the operating point )(t o be given by the following Controlled Auto-Regressive Integrated Moving Average (CARIMA) model:)()()()()()(111t e z C t u z B z t y z A d ----+∆= (2) Where )()(),()(1111----∆=z andC z B z A z A are polynomials in 1-z , the backward shift operator. Note that the coefficients of these polynomials are a function of the operating point )(t o .The nonlinear system (1) is partitioned into several operating regions, such that each region can be approximated by a local linear model. Since NFN is a class of associative memory networks with knowledge stored locally, they can be applied to model this class of nonlinear systems. A schematic diagram of the NFN is shown in Fig.2.B-spline functions are used as the membership functions in theNFN for the following reasons. First, B-spline functions can be readily specified by the order of the basis function and the number of inner knots. Second, they are defined on a bounded support, and the output of the basis function is always positive, i.e.,],[,0)(j k j j k x x λλμ-∉=and ],[,0)(j k j j k x x λλμ-∈>.Third, the basis functions form a partition of unity, i.e.,.][,1)(min,∑∈≡j mam j k x x x x μ(3)And fourth, the output of the basis functions can be obtained by a recurrence equation.Fig. 2 neuro-fuzzy network The membership functions of the fuzzy variables derived from the fuzzy rules can be obtained by the tensor product of the univariate basis functions. As an example, consider the NFN shown in Fig.2, which consists of the following fuzzy rules: IF operating condition i (1x is positive small, ... , and n x is negative large),THEN the output is given by the local CARIMA model i:...)()(ˆ...)1(ˆ)(ˆ01+-∆+-++-=d t u b n t y a t y a t yi i a i in i i i a )(...)()(c i in i b i in n t e c t e n d t u b c b -+++--∆+ (4)or )()()()()(ˆ)(111t e z C t u z B z t yz A i i i i d i i ----+∆= (5) Where )()(),(111---z andC z B z A i i i are polynomials in the backward shift operator 1-z , and d is the dead time of the plant,)(t u i is the control, and )(t e i is a zero mean independent random variable with a variance of 2δ. The multivariate basis function )(k i x a is obtained by the tensor products of the univariate basis functions,p i x A a nk k i k i ,...,2,1,)(1==∏=μ (6)where n is the dimension of the input vector x , and p , the total number of weights in the NFN, is given by,∏=+=nk i i k R p 1)( (7)Where i k and i R are the order of the basis function and the number of inner knots respectively. The properties of the univariate B-spline basis functions described previously also apply to the multivariate basis function, which is defined on the hyper-rectangles. The output of the NFN is,∑∑∑=====p i i i p i ip i i i a y aa yy 111ˆˆˆ (8) 3. Neuro-fuzzy modelling and predictive control of superheatedsteam temperatureLet θbe the superheated steam temperature, and θμ, the flow of spray water to the high temperature superheater. The response of θcan be approximated by a second order model:The linear models, however, only a local model for the selected operating point. Since load is the unique antecedent variable, it is used to select the division between the local regions in the NFN. Based on this approach, the load is divided into five regions as shown in Fig.3,using also the experience of the operators, who regard a load of 200MW as high,180MW as medium high,160MW as medium,140MW as medium low and 120MW as low. For a sampling interval of 30s , the estimated linear local models )(1-z A used in the NFN are shown in Table 1.Fig. 3 Membership function for local modelsTable 1 Local CARIMA models in neuro-fuzzy modelCascade control scheme is widely used to control the superheated steam temperature. Feed forward control, with the steam flow and the gas temperature as inputs, can be applied to provide a faster response to large variations in these two variables. In practice, the feed forward paths are activated only when there are significant changes in these variables. The control scheme also prevents the faster dynamics of the plant, i.e., the spray water valve and the water/steam mixing, from affecting the slower dynamics of the plant, i.e., the high temperature superheater. With the global nonlinear NFN model in Table 1, the proposed NFGPC scheme is shown in Fig.4.Fig. 4 NFGPC control of superheated steam temperature with feed-for-ward control.As a further illustration, the power plant is simulated using the NFN model given in Table 1,and is controlled respectively by the NFGPC, the conventional linear GPC controller, and the cascaded PI controller while the load changes from 160MW to 200MW.The conventional linear GPC controller is the local controller designed for the“medium”operating region. The results are shown in Fig.5,showing that, as expected, the best performance is obtained from the NFGPC as it is designed based on a more accurate process model. This is followed by the conventional linear GPC controller. The performance of the conventional cascade PI controller is the worst, indicating that it is unable to control satisfactory the superheated steam temperature under large load changes. This may be the reason for controlling the power plant manually when there are large load changes.Fig.5 comparison of the NFGPC, conventional linear GPC, and cascade PI controller.4. ConclusionsThe modeling and control of a 200 MW power plant using the neuro-fuzzy approach is presented in this paper. The NFN consists of five local CARIMA models.The out-put of the network is the interpolation of the local models using memberships given by the B-spline basis functions. The proposed NFGPC is similarly constructed, which is designed from the CARIMA models in the NFN. The NFGPC is most suitable for processes with smooth nonlinearity, such that its full operating range can be partitioned into several local linear operating regions. The proposed NFGPC therefore provides a useful alternative for controlling this class of nonlinear power plants, which are formerly difficult to be controlled using traditional methods.Part 4 为Part3译文：锅炉蒸汽温度模糊神经网络的广义预测控制Xiangjie LIU, Jizhen LIU, Ping GUAN摘要：发电厂是非线性和不确定性的复杂系统。

电气工程与自动化毕业论文中英文资料外文翻译

电气工程与自动化毕业论文中英文资料外文翻译The Transformer on load ﹠Introduction to DC MachinesIt has been shown that a primary input voltage 1V can be transformed to any desired open-circuit secondary voltage 2E by a suitable choice of turns ratio. 2E is available for circulating a load current impedance. For the moment, a lagging power factor will be considered. The secondary current and the resulting ampere-turns 22N I will change the flux, tending to demagnetize the core, reduce m Φ and with it 1E . Because the primary leakage impedance drop is so low, a small alteration to 1Ewill cause an appreciable increase of primary current from 0I to a new value of 1Iequal to ()()i jX R E V ++111/. The extra primary current and ampere-turns nearly cancel the whole of the secondary ampere-turns. This being so , the mutual flux suffers only a slight modification and requires practically the same net ampere-turns 10N I as on no load. The total primary ampere-turns are increased by an amount 22N I necessary to neutralize the same amount of secondary ampere-turns. In thevector equation , 102211N I N I N I =+; alternatively, 221011N I N I N I -=. At full load,the current 0I is only about 5% of the full-load current and so 1I is nearly equalto 122/N N I . Because in mind that 2121/N N E E =, the input kV A which is approximately 11I E is also approximately equal to the output kV A, 22I E .The physical current has increased, and with in the primary leakage flux towhich it is proportional. The total flux linking the primary ,111Φ=Φ+Φ=Φm p , isshown unchanged because the total back e.m.f.,（dt d N E /111Φ-）is still equal and opposite to 1V . However, there has been a redistribution of flux and the mutual component has fallen due to the increase of 1Φ with 1I . Although the change is small, the secondary demand could not be met without a mutual flux and e.m.f.alteration to permit primary current to change. The net flux s Φlinking thesecondary winding has been further reduced by the establishment of secondaryleakage flux due to 2I , and this opposes m Φ. Although m Φ and 2Φ are indicatedseparately , they combine to one resultant in the core which will be downwards at theinstant shown. Thus the secondary terminal voltage is reduced to dt d N V S /22Φ-=which can be considered in two components, i.e. dt d N dt d N V m //2222Φ-Φ-=orvectorially 2222I jX E V -=. As for the primary, 2Φ is responsible for a substantiallyconstant secondary leakage inductance222222/Λ=ΦN i N . It will be noticed that the primary leakage flux is responsible for part of the change in the secondary terminal voltage due to its effects on the mutual flux. The two leakage fluxes are closely related; 2Φ, for example, by its demagnetizing action on m Φ has caused the changes on the primary side which led to the establishment of primary leakage flux.If a low enough leading power factor is considered, the total secondary flux and the mutual flux are increased causing the secondary terminal voltage to rise with load. p Φ is unchanged in magnitude from the no load condition since, neglecting resistance, it still has to provide a total back e.m.f. equal to 1V . It is virtually the same as 11Φ, though now produced by the combined effect of primary and secondary ampere-turns. The mutual flux must still change with load to give a change of 1E and permit more primary current to flow. 1E has increased this time but due to the vector combination with 1V there is still an increase of primary current.Two more points should be made about the figures. Firstly, a unity turns ratio has been assumed for convenience so that '21E E =. Secondly, the physical picture is drawn for a different instant of time from the vector diagrams which show 0=Φm , if the horizontal axis is taken as usual, to be the zero time reference. There are instants in the cycle when primary leakage flux is zero, when the secondary leakage flux is zero, and when primary and secondary leakage flux is zero, and when primary and secondary leakage fluxes are in the same sense.The equivalent circuit already derived for the transformer with the secondary terminals open, can easily be extended to cover the loaded secondary by the addition of the secondary resistance and leakage reactance.Practically all transformers have a turns ratio different from unity although such an arrangement is sometimes employed for the purposes of electrically isolating one circuit from another operating at the same voltage. To explain the case where 21N N ≠ the reaction of the secondary will be viewed from the primary winding. The reaction is experienced only in terms of the magnetizing force due to the secondary ampere-turns. There is no way of detecting from the primary side whether 2I is large and 2N small or vice versa, it is the product of current and turns which causesthe reaction. Consequently, a secondary winding can be replaced by any number of different equivalent windings and load circuits which will give rise to an identical reaction on the primary .It is clearly convenient to change the secondary winding to an equivalent winding having the same number of turns 1N as the primary.With 2N changes to 1N , since the e.m.f.s are proportional to turns, 2212)/('E N N E = which is the same as 1E .For current, since the reaction ampere turns must be unchanged 1222'''N I N I = must be equal to 22N I .i.e. 2122)/(I N N I =.For impedance , since any secondary voltage V becomes V N N )/(21, and secondary current I becomes I N N )/(12, then any secondary impedance, including load impedance, must becomeI V N N I V /)/('/'221=. Consequently,22212)/('R N N R = and 22212)/('X N N X = . If the primary turns are taken as reference turns, the process is called referring to the primary side.There are a few checks which can be made to see if the procedure outlined is valid.For example, the copper loss in the referred secondary winding must be the same as in the original secondary otherwise the primary would have to supply a differentloss power. ''222R I must be equal to 222R I . ）222122122/()/(N N R N N I •• does infact reduce to 222R I .Similarly the stored magnetic energy in the leakage field)2/1(2LI which is proportional to 22'X I will be found to check as ''22X I . The referred secondary 2212221222)/()/(''I E N N I N N E I E kVA =•==.The argument is sound, though at first it may have seemed suspect. In fact, if the actual secondary winding was removed physically from the core and replaced by the equivalent winding and load circuit designed to give the parameters 1N ,'2R ,'2X and '2I , measurements from the primary terminals would be unable to detect any difference in secondary ampere-turns, kVA demand or copper loss, under normal power frequency operation.There is no point in choosing any basis other than equal turns on primary andreferred secondary, but it is sometimes convenient to refer the primary to the secondary winding. In this case, if all the subscript 1’s are interchanged for the subscript 2’s, the necessary referring constants are easily found; e.g. 2'1R R ≈,21'X X ≈; similarly 1'2R R ≈ and 12'X X ≈.The equivalent circuit for the general case where 21N N ≠ except that m r hasbeen added to allow for iron loss and an ideal lossless transformation has been included before the secondary terminals to return '2V to 2V .All calculations of internal voltage and power losses are made before this ideal transformation is applied. The behaviour of a transformer as detected at both sets of terminals is the same as the behaviour detected at the corresponding terminals of this circuit when the appropriate parameters are inserted. The slightly different representation showing the coils 1N and 2N side by side with a core in between is only used for convenience. On the transformer itself, the coils are , of course , wound round the same core.Very little error is introduced if the magnetising branch is transferred to the primary terminals, but a few anomalies will arise. For example ,the current shown flowing through the primary impedance is no longer the whole of the primary current.The error is quite small since 0I is usually such a small fraction of 1I . Slightlydifferent answers may be obtained to a particular problem depending on whether or not allowance is made for this error. With this simplified circuit, the primary and referred secondary impedances can be added to give:221211)/(Re N N R R += and 221211)/(N N X X Xe +=It should be pointed out that the equivalent circuit as derived here is only valid for normal operation at power frequencies; capacitance effects must be taken into account whenever the rate of change of voltage would give rise to appreciablecapacitance currents, dt CdV I c /=. They are important at high voltages and atfrequencies much beyond 100 cycles/sec. A further point is not the only possible equivalent circuit even for power frequencies .An alternative , treating the transformer as a three-or four-terminal network, gives rise to a representation which is just as accurate and has some advantages for the circuit engineer who treats all devices as circuit elements with certain transfer properties. The circuit on this basiswould have a turns ratio having a phase shift as well as a magnitude change, and the impedances would not be the same as those of the windings. The circuit would not explain the phenomena within the device like the effects of saturation, so for an understanding of internal behaviour .There are two ways of looking at the equivalent circuit:(a) viewed from the primary as a sink but the referred load impedance connected across '2V ,or(b) viewed from the secondary as a source of constant voltage 1V with internal drops due to 1Re and 1Xe . The magnetizing branch is sometimes omitted in this representation and so the circuit reduces to a generator producing a constant voltage 1E (actually equal to 1V ) and having an internal impedance jX R + (actually equal to 11Re jXe +).In either case, the parameters could be referred to the secondary winding and this may save calculation time .The resistances and reactances can be obtained from two simple light load tests. Introduction to DC MachinesDC machines are characterized by their versatility. By means of various combination of shunt, series, and separately excited field windings they can be designed to display a wide variety of volt-ampere or speed-torque characteristics for both dynamic and steadystate operation. Because of the ease with which they can be controlled , systems of DC machines are often used in applications requiring a wide range of motor speeds or precise control of motor output.The essential features of a DC machine are shown schematically. The stator has salient poles and is excited by one or more field coils. The air-gap flux distribution created by the field winding is symmetrical about the centerline of the field poles. This axis is called the field axis or direct axis.As we know , the AC voltage generated in each rotating armature coil is converted to DC in the external armature terminals by means of a rotating commutator and stationary brushes to which the armature leads are connected. The commutator-brush combination forms a mechanical rectifier, resulting in a DCarmature voltage as well as an armature m.m.f. wave which is fixed in space. The brushes are located so that commutation occurs when the coil sides are in the neutral zone , midway between the field poles. The axis of the armature m.m.f. wave then in 90 electrical degrees from the axis of the field poles, i.e., in the quadrature axis. In the schematic representation the brushes are shown in quarature axis because this is the position of the coils to which they are connected. The armature m.m.f. wave then is along the brush axis as shown.. (The geometrical position of the brushes in an actual machine is approximately 90 electrical degrees from their position in the schematic diagram because of the shape of the end connections to the commutator.)The magnetic torque and the speed voltage appearing at the brushes are independent of the spatial waveform of the flux distribution; for convenience we shall continue to assume a sinusoidal flux-density wave in the air gap. The torque can then be found from the magnetic field viewpoint.The torque can be expressed in terms of the interaction of the direct-axis air-gapflux per pole d Φ and the space-fundamental component 1a F of the armature m.m.f.wave . With the brushes in the quadrature axis, the angle between these fields is 90 electrical degrees, and its sine equals unity. For a P pole machine 12)2(2a d F P T ϕπ=In which the minus sign has been dropped because the positive direction of thetorque can be determined from physical reasoning. The space fundamental 1a F ofthe sawtooth armature m.m.f. wave is 8/2π times its peak. Substitution in above equation then givesa d a a d a i K i m PC T ϕϕπ==2 Where a i =current in external armature circuit;a C =total number of conductors in armature winding;m =number of parallel paths through winding;Andm PC K aa π2=Is a constant fixed by the design of the winding.The rectified voltage generated in the armature has already been discussedbefore for an elementary single-coil armature. The effect of distributing the winding in several slots is shown in figure ,in which each of the rectified sine waves is the voltage generated in one of the coils, commutation taking place at the moment when the coil sides are in the neutral zone. The generated voltage as observed from the brushes is the sum of the rectified voltages of all the coils in series between brushesand is shown by the rippling line labeled a e in figure. With a dozen or socommutator segments per pole, the ripple becomes very small and the average generated voltage observed from the brushes equals the sum of the average values ofthe rectified coil voltages. The rectified voltage a e between brushes, known also asthe speed voltage, ism d a m d a a W K W m PC e ϕϕπ==2 Where a K is the design constant. The rectified voltage of a distributed winding has the same average value as that of a concentrated coil. The difference is that the ripple is greatly reduced.From the above equations, with all variable expressed in SI units:m a a Tw i e =This equation simply says that the instantaneous electric power associated with the speed voltage equals the instantaneous mechanical power associated with the magnetic torque , the direction of power flow being determined by whether the machine is acting as a motor or generator.The direct-axis air-gap flux is produced by the combined m.m.f. f f i N ∑ of the field windings, the flux-m.m.f. characteristic being the magnetization curve for the particular iron geometry of the machine. In the magnetization curve, it is assumed that the armature m.m.f. wave is perpendicular to the field axis. It will be necessary to reexamine this assumption later in this chapter, where the effects of saturation are investigated more thoroughly. Because the armature e.m.f. is proportional to flux times speed, it is usually more convenient to express the magnetization curve in termsof the armature e.m.f. 0a e at a constant speed 0m w . The voltage a e for a given fluxat any other speed m w is proportional to the speed,i.e. 00a m m a e w w e =Figure shows the magnetization curve with only one field winding excited. This curve can easily be obtained by test methods, no knowledge of any design details being required.Over a fairly wide range of excitation the reluctance of the iron is negligible compared with that of the air gap. In this region the flux is linearly proportional to the total m.m.f. of the field windings, the constant of proportionality being the direct-axis air-gap permeance.The outstanding advantages of DC machines arise from the wide variety of operating characteristics which can be obtained by selection of the method of excitation of the field windings. The field windings may be separately excited from an external DC source, or they may be self-excited; i.e., the machine may supply its own excitation. The method of excitation profoundly influences not only the steady-state characteristics, but also the dynamic behavior of the machine in control systems.The connection diagram of a separately excited generator is given. The required field current is a very small fraction of the rated armature current. A small amount of power in the field circuit may control a relatively large amount of power in the armature circuit; i.e., the generator is a power amplifier. Separately excited generators are often used in feedback control systems when control of the armature voltage over a wide range is required. The field windings of self-excited generators may be supplied in three different ways. The field may be connected in series with the armature, resulting in a shunt generator, or the field may be in two sections, one of which is connected in series and the other in shunt with the armature, resulting in a compound generator. With self-excited generators residual magnetism must be present in the machine iron to get the self-excitation process started.In the typical steady-state volt-ampere characteristics, constant-speed primemovers being assumed. The relation between the steady-state generated e.m.f. a Eand the terminal voltage t V isa a a t R I E V -=Where a I is the armature current output and a R is the armature circuitresistance. In a generator, a E is large than t V ; and the electromagnetic torque T is acountertorque opposing rotation.The terminal voltage of a separately excited generator decreases slightly with increase in the load current, principally because of the voltage drop in the armature resistance. The field current of a series generator is the same as the load current, so that the air-gap flux and hence the voltage vary widely with load. As a consequence, series generators are not often used. The voltage of shunt generators drops off somewhat with load. Compound generators are normally connected so that the m.m.f. of the series winding aids that of the shunt winding. The advantage is that through the action of the series winding the flux per pole can increase with load, resulting in a voltage output which is nearly constant. Usually, shunt winding contains many turns of comparatively heavy conductor because it must carry the full armature current of the machine. The voltage of both shunt and compound generators can be controlled over reasonable limits by means of rheostats in the shunt field. Any of the methods of excitation used for generators can also be used for motors. In the typical steady-state speed-torque characteristics, it is assumed that the motor terminals are supplied froma constant-voltage source. In a motor the relation between the e.m.f. a E generated inthe armature and the terminal voltage t V isa a a t R I E V +=Where a I is now the armature current input. The generated e.m.f. a E is nowsmaller than the terminal voltage t V , the armature current is in the oppositedirection to that in a motor, and the electromagnetic torque is in the direction to sustain rotation of the armature.In shunt and separately excited motors the field flux is nearly constant. Consequently, increased torque must be accompanied by a very nearly proportional increase in armature current and hence by a small decrease in counter e.m.f. to allow this increased current through the small armature resistance. Since counter e.m.f. is determined by flux and speed, the speed must drop slightly. Like the squirrel-cage induction motor ,the shunt motor is substantially a constant-speed motor having about 5 percent drop in speed from no load to full load. Starting torque and maximum torque are limited by the armature current that can be commutatedsuccessfully.An outstanding advantage of the shunt motor is ease of speed control. With a rheostat in the shunt-field circuit, the field current and flux per pole can be varied at will, and variation of flux causes the inverse variation of speed to maintain counter e.m.f. approximately equal to the impressed terminal voltage. A maximum speed range of about 4 or 5 to 1 can be obtained by this method, the limitation again being commutating conditions. By variation of the impressed armature voltage, very wide speed ranges can be obtained.In the series motor, increase in load is accompanied by increase in the armature current and m.m.f. and the stator field flux (provided the iron is not completely saturated). Because flux increases with load, speed must drop in order to maintain the balance between impressed voltage and counter e.m.f.; moreover, the increase in armature current caused by increased torque is smaller than in the shunt motor because of the increased flux. The series motor is therefore a varying-speed motor with a markedly drooping speed-load characteristic. For applications requiring heavy torque overloads, this characteristic is particularly advantageous because the corresponding power overloads are held to more reasonable values by the associated speed drops. Very favorable starting characteristics also result from the increase in flux with increased armature current.In the compound motor the series field may be connected either cumulatively, so that its.m.m.f.adds to that of the shunt field, or differentially, so that it opposes. The differential connection is very rarely used. A cumulatively compounded motor has speed-load characteristic intermediate between those of a shunt and a series motor, the drop of speed with load depending on the relative number of ampere-turns in the shunt and series fields. It does not have the disadvantage of very high light-load speed associated with a series motor, but it retains to a considerable degree the advantages of series excitation.The application advantages of DC machines lie in the variety of performance characteristics offered by the possibilities of shunt, series, and compound excitation. Some of these characteristics have been touched upon briefly in this article. Stillgreater possibilities exist if additional sets of brushes are added so that other voltages can be obtained from the commutator. Thus the versatility of DC machine systems and their adaptability to control, both manual and automatic, are their outstanding features.中文翻译负载运行的变压器及直流电机导论通过选择合适的匝数比，一次侧输入电压1V 可任意转换成所希望的二次侧开路电压2E 。

自动化毕业设计英文翻译

自动化毕业设计英文翻译Automatic Graduation Project TranslationIntroductionIn today's fast-paced world, automation has become an integral part of various industries. It has revolutionized the way we work and has significantly improved efficiency and productivity. As a result, automation has become a popular choice for graduation projects among engineering students. In this article, we will delve into the topic of automatic graduation project translation and explore its significance and benefits.The Significance of Automatic Graduation Project TranslationAutomatic graduation project translation refers to the use of automated tools and techniques to translate project documentation and reports from one language to another. This process eliminates the need for manual translation, saving time and effort for students. Moreover, it ensures accuracy and consistency in the translation, reducing the risk of misinterpretation.Benefits of Automatic Graduation Project Translation1. Time-saving: Manual translation can be a time-consuming task, especially when dealing with lengthy project documents. By utilizing automatic translation tools, students can significantly reduce the time spent on translation, allowing them to focus on other important aspects of their project.2. Improved accuracy: Automated translation tools use advanced algorithms and machine learning techniques to ensure accurate translations. These tools havethe ability to learn from previous translations and improve their accuracy over time. This reduces the chances of errors and ensures the quality of the translated content.3. Cost-effective: Hiring professional translators can be expensive, especially for students on a limited budget. Automatic translation tools provide a cost-effective solution, as they are often available for free or at a minimal cost. This allows students to allocate their resources efficiently and invest in other project requirements.4. Enhanced collaboration: Automatic translation tools facilitate seamless collaboration among team members who may speak different languages. By translating project documentation, everyone can understand and contribute to the project without any language barriers. This promotes effective teamwork and improves overall project outcomes.Challenges and LimitationsWhile automatic graduation project translation offers numerous benefits, it is important to acknowledge its challenges and limitations. Some of these include: 1. Language nuances: Automated translation tools may struggle to accurately capture the nuances and subtleties of a language. This can result in the loss of context and potential misinterpretation of the translated content. Therefore, it is crucial for students to review and edit the translated material to ensure its accuracy.2. Technical jargon: Engineering projects often involve complex technical jargonand terminology. Automated translation tools may not have the capability to accurately translate these specialized terms. Students must be cautious and manually review the translated content to ensure the technical accuracy of their project documentation.3. Cultural differences: Different cultures have unique ways of expressing ideas and concepts. Automated translation tools may not always be able to capture these cultural nuances, leading to misunderstandings or misinterpretations. Students should be aware of these differences and make necessary adjustments to ensure effective communication.ConclusionAutomatic graduation project translation offers students a convenient and efficient way to translate project documentation. It saves time, improves accuracy, and promotes collaboration among team members. However, it is important to recognize the limitations of automated translation tools and take necessary precautions to ensure the quality and accuracy of the translated content. By leveraging the benefits of automatic translation while being mindful of its limitations, students can enhance their graduation projects and contribute to the advancement of automation in the engineering field.。

自动化专业毕业设计外文翻译--现地控制单元在水电厂自动化中的应用

英文资料及翻译Location Control Unit In Hydroelectric PowerPlant Automation Application1. ForewordThe hydraulic electricity generation compares with burns coal, the fuel oil, the nuclear power electricity generation, the energy is renewable, the never exhaustible clean energy. The country gives priority to development the hydraulic electricity generation achievement to do well at present the energy balance the strategic measure, and appeared a row measure to encourage to advance the hydroelectric power plant construction vigorously. In the water and electricity profession, was on duty " along with hydroelectric power plant " nobody (few person value to defend) and the condition overhaul work thoroughly develops unceasingly, adds water the power plant production to move and to manage set a higher request; “Separated take the factory net, competes the price to access the net” also adds water as the foundation electric power system reform the power plant automation technology to set the new request. Computer technology, information technology, networking, industry control technology rapid development, for hydroelectric power plant synthesis automated system regardless of in the structure in the function, has all provided a broad development space.The 70's intermediate stages, the overseas hydroelectric power plant starts the advanced computer technology to apply in the hydro-electric power station industrial control, raised the hydroelectric power plant automated level greatly, has obtained the good economic efficiency. At the end of the 70's, the original electric power department science and technology committee managed held “the national hydroelectric power plant automation technical background meeting”, formulated the hydroelectric power plant automation science and technology to develop 7 years plan, our country starts to introduce and the domestic independent research and development hydroelectric power plant computer supervisory system technology and to obtain the huge success. Through many year endeavors, the domestic independent development hydroelectric power plant automation technology development experienced had tried to find out, the experiment site, the promotion, enhanced these four stages, has obtained the very big result. In the recent 20 years, the domestic hydroelectric power plant automation level development are specially rapid, at present entered the world advanced ranks.The hydroelectric power plant computer supervisory system usually may divide into two major parts, one is carries on the common control to the entire factory equipment the part, calls it the factory level or the factory station level supervisory system; Another part is located the water wheel electricity generation level, the switching house and so on the equipment nearby control sections, is called the location control system. The location control system main constituent is location control unit LCU (Local Control Unit), the early on once has used with electrical network dispatch remote terminal RTU (Remote Terminal Unit) the similar name, considered LCU the meaning is more accurate, since 1991 “location control unit academic conference”, basically unifies calls it LCU. Now makes several discussions on LCU in Our country Hydroelectric powerplant automated system application and the development.2. LCU applicationIn the hydroelectric power plant computer supervisory system LCU with the power plant production process connection, is directly in the system most has the object-oriented distribution characteristic the control device. The location control unit controlled member mainly includes following several parts:(1) power plant generating set, mainly has the hydraulic turbine, the generator, the auxiliary engine, the transformer and so on;(2) switching house, mainly has the generatrix, the circuit breaker, the isolator, the earth knife switch and so on;(3) public utility, mainly has the factory to use electricity the system, the oil system, the aqueous system, the direct current system and so on;(4) strobe, mainly has the water inlet strobe, the flood discharge strobe and so on.The LCU general arrangement nearby the power plant production equipment, to is accused the object movement operating mode to carry on the real-time surveillance and the control, is the power plant computer supervisory system compares the first floor control section. The primary data carries on gathering and the pretreatment in this, each kind of control adjustment order all sends out and completes the control closed loop through it, it is in the entire supervisory system very important, to the reliable request very high control device. Uses in the hydroelectric power plant LCU may divide into unit LCU, public LCU, switching house LCU according to the monitoring object and the installment position and so on. But and disposes according to the LCU itself structure divides, then may divide into the single trigger --linear structure LCU, take programmable controller (PLC) as foundation LCU, the intelligent location controller and so on three kinds. First kind of LCU many for hydroelectric power plant automation initial period product, at present basic no longer has used in the new system. Moreover still had few small hydroelectric power plants to use based on industry PC machine (called labor controlled machine IPC) the control system, below only discussed is in the mainstream status PLC and the intelligent location controller (the recent several years still had is called PCC (Programmable Computer Controller), PAC (Programmable Automation Controller) product, should also be possible to classify).2.1 programmable controller (PLC)The PLC definition has many kinds. International electrician committee (IEC) to PLC the definition is: The programmable controller is one kind of digital operation electronic system, for designs specially in the industry environment application. It uses the programmable the memory, uses in its internally stored program, carries out the logic operation, the sequential control, fixed time, counts with the arithmetic operation and so on face user's instruction, and through digital, the simulation input and the output, controls each kind of type the machinery or the production process. The programmable controller and the related equipment, all should according to easy form a whole with the industry control system, easy to expand its function the principle design.At first, needed to produce as a result of the American automobile industry has been possible to say was primitive PLC. Although the PLC being published time does not calculate long too, but along with the microprocessor appearance, large-scale, the ultra large scale integrated circuit technique of manufacture and the data communication technology rapid development, the PLC application and the technology also obtained the rapid development, its developing processapproximately separable three stages:(1) early time PLC (at the end of 60's -70's intermediate stages): Early PLC is called the programmable logical controller generally.(2) intermediate stage PLC (in 70's intermediate stage - 80's, later period): Starts in the 70's to use the microprocessor to take PLC the central processing element (CPU). Thus, causes PLC to result in the function big enhancement. In the software aspect, in the original logic operation, fixed time, counted and so on in the function foundations to increase functions and so on arithmetic operation, data processing and data communication, from diagnosis. In the hardware aspect, has developed the simulation quantity module, the long-distance I/O module as well as each kind of special function module, enables PLC the application scope to expand rapidly to needs the automatic control very many professions.(3) near future PLC (in the 80's, later period until now) enters in for the 80's, the later period, because the microprocessor hardware technique of manufacture rapid development, simultaneously the market price large scale drop, will cause each PLC manufacturer to be possible to use a higher scale the microprocessor. In order to further enhance PLC the processing speed, the very many manufacture manufacturer also developed has developed the special-purpose logical processing chip. Afterwards PLC has also integrated Ethernet, technologies and so on Web Server, has provided the function rich necessary software, causes the user community to use handily.On the century 80's to the 90's intermediate stages, are PLC develops the quickest time, the yearly rate continuously maintenance is 30%~40%. In this time, the PLC data acquisition handling ability, the numeral operational capability, the man-machine connection and network traffic capacity all obtains the large scale enhancement, PLC enters the process control domain gradually, unified after the partial industry control device substitutes gradually in certain applications has been at the dominant position in the process control domain the DCS system. Because PLC has the versatility strongly, the reliability high, the easy to operate, the programming simple, the adaptation surface broad and so on the characteristics, caused it is specially in the sequential control obtained the extremely widespread application in the industrial automation control.Applies PLC in the hydroelectric power plant production equipment monitoring begins in on the century 80's, because PLC defers to the industry use environment the standard to carry on the design generally, the reliability high, antijamming ability strong, the programming simple practical, met inserts the performance good very quickly accepts by the power plant user and system integration business, obtained the good application. At present includes in Our country Hydroelectric power plant use widespread PLC: GE Fanuc Corporation's GE Fanuc 90 series, German Siemens Corporation's S5, S7 series, French Schneider Corporation's Modicon Premium, Atrium and Quantum, American Rockwell Corporation PLC5, Control Logix, Japanese OMRON Corporation's SU-5, SU-6, SU-8, Japanese MITSUBISHI Corporation's FX2 series and so on. Because each kind of PLC principle of design difference is big, the product function, the performance as well as may constitute the location system scale to have the very big difference. Generally speaking, according to the different power plant in the security performance (including reliability, maintainable and so on), aspect and so on application function, control scale, system structure actual demands carries on the choice, may find appropriate PLC. At present there is big part of power plants the automated system all uses the PLC constitution location control section, and matches through the reasonable disposition, they basically all can shoulder the corresponding responsibility in the system, completes the corresponding function.But PLC took but one kind of general automated installment, is by no means designs specially for the hydroelectric power plant automation, this has in the special request profession application in the water and electricity automation also to be able to have some not suitable place inevitably, presently lists following several points:(1) PLC by “scanning”the way work, cannot satisfy the event resolution and the system clock synchronization request. The hydroelectric power plant computer supervisory system all is a multi-computer system, in order to guarantee the event resolution should have certain event besides PLC itself to respond ability and the high accuracy clock, but also requests in the overall system between various part of main equipment clock synthesis precision also to have to guarantee in a millisecond level. But take PLC as the foundation location control device if does not take the special measure, is unable to guarantee the hydroelectric power plant safe operation to the event resolution and the system clock synchronization request.(2) general PLC origin mainly aims at the machine-finishing profession, later gradually will expand all the various trades and occupations. Although present PLC has strongly from diagnosis function, but regarding the input, the output unit, it only from diagnoses the module level. This produces this kind of emphasis regarding our country electric power “the safety first” the profession said that, has certain being short of, often needs to add seperately the special security measure.(3) general PLC all has certain surge suppression ability generally, basically may suit the majority of profession application. But says regarding the hydroelectric power plant automated system, as a result of the equipment working conditions particularity, three level of surge suppression ability which the general PLC surge suppression ability and the technology standard request also has some disparities.2.2 intelligent location controllerApplies the many another kind of location control unit in Hydroelectric power plant automated system to be supposed to be the intelligent location controller, like ABB Corporation AC450, south auspicious group's SJ-600 series, Elin Corporation's SAT1703 and so on.AC450 is being suitable which ABB Corporation produces in industry environment Advant Controller series location control unit one kind, mainly applies in other profession DCS. It has included the module which by Motorola 68040 primarily processor CPU modules and I/O, MasterBus and so on many kinds of may elect, supports centralized I/O and distributional I/O, may act according to the different application demand to use the different module to constitute the suitable location subsystem.SAT1703 is the multi-processor system which Austrian Elin Corporation produces, it is loaded with different connection processor subsystem AK1703, AME1703 and AM1703 including 3. Each sub-system by the host processor, the connection template (module), constitutions and so on connection module, can realize the data processing, the control and the correspondence function, uses SMI in the LCU interior (Serial Module Interconnector) to carry on the correspondence. SAT1703 location control unit uses OS/2 operating system, the movement control software is ToolBox.SJ-600 series is on the international telegram automation research institute the century at the end of 90's for the domestically produced intelligence distributional location control unit which moves under the bad industry environment produces, by the master control module, the intelligent I/O module, the power source module as well as connects various modules and the master controlmodule scene bus network is composed. Moved reliably in the national dozens of large and middle scale hydroelectric power plants. Below SJ-600 has the main characteristic:(1), the master control module uses conforms to IEEE1996.1's embedded module standard PC104, has the reliability high, the scene environment compatibility strong and so on the characteristics. Uses low power loss embedded CPU, may choose the CPU model from 486 to the Pentium series.(2) 32 intelligence I/O module. All modules use 32 embedded CPU, this CPU designs specially for the embedded control, on the software uses the board level real-time operating system and the unification procedure code, only is different moves the corresponding duty according to the module. Has used large-scale programmable logic chip (EPLD) and the Flash memory, simplified the system design, enhanced the reliability. The intellectualized I/O module except may complete the data acquisition and the pretreatment independently, but also has very strongly from the diagnosis function, has provided the reliable control security and the convenience breakdown localization ability.(3) has the field bus network system structure, the system uses two network architectures, first is the factory cascade control network, connects LCU and the factory level computer, constitutes the distributed computer supervisory system; Second is I/O main line network, the connection master control module and the intelligent I/O module (location or long-distance), constitutes the distributional location control subsystem. All I/O module provides two field bus network connection, these modules all may disperse the arrangement, forms the redundant reliable distributional redundant system.(4) LCU direct connection high speed network. The network has become in the computer supervisory system the important part, it involves to the power plant control strategy and the movement way. Beforehand location controller many is the use private network carries on the connection with on position machine system, but conforms to the open standard network. If AC450 uses MB300 network with on position machine system connection, but with uses TCP/IP agreement the system connection only to be able to carry on through the special-purpose module by the VIP way the data transmission which limits.(5) has provided the direct GPS synchronized clock connection, does not need to program and the establishment. GPS to when may go directly to the module level, satisfied had the special request situation to the clock, like SOE and so on.(6) provides based on IEC61131-3 standard control language, in retained trapezoidal programming language in and so on the chart, structure text, instruction list foundations, developed the use “to see namely obtained”the technical design visualization flow chart programming language. The support control flow online debugging and playbacking, suits the complex control flow extremely the production and the maintenance.(7) in view of hydroelectric power plant automation specialized application development special-purpose function module.现地控制单元在水电厂自动化中的应用1. 前言水力发电与燃煤、燃油、核能发电相比，能源是可再生的、永不枯竭的清洁能源。

电气工程及其自动化专业毕业论文外文翻译

本科毕业设计(论文)中英文对照翻译院(系部）工程学院专业名称电气工程及其自动化年级班级 11级2班学生姓名蔡李良指导老师赵波Infrared Remote Control SystemAbstractRed outside data correspondence the technique be currently within the scope of world drive extensive usage of a kind of wireless conjunction technique, drive numerous hardware and software platform support。

Red outside the transceiver product have cost low，small scaled turn, the baud rate be quick，point to point SSL, be free from electromagnetism thousand Raos etc. characteristics，can realization information at dissimilarity of the product fast，convenience，safely exchange and transmission, at short distance wireless deliver aspect to own very obvious of advantage。

Along with red outside the data deliver a technique more and more mature, the cost descend, red outside the transceiver necessarily will get at the short distance communication realm more extensive of application.The purpose that design this s ystem is transmit customer’s operation information with infrared rays for transmit media, then demodulate original signal with receive circuit。

自动化专业外文翻译----温度控制简介和PID控制器

毕业设计（论文）外文资料翻译系别：电气工程系专业：电气工程及其自动化班级：姓名：学号：外文出处：Specialized English For ArchitecturalElectric Engineering and Automation附件：1、外文原文；2、外文资料翻译译文。

1、外文原文Introductions to temperature control and PID controllersProcess control system.Automatic process control is concerned with maintaining process variables temperatures pressures flows compositions, and the like at some desired operation value. Processes are dynamic in nature. Changes are always occurring, and if actions are nottaken, the important process variables-those related to safety, product quality, and production rates-will not achieve design conditions.In order to fix ideas, let us consider a heat exchanger in which a process stream is heated by condensing steam. The process is sketched in Fig.1Fig. 1 Heat exchangerThe purpose of this unit is to heat the process fluid from some inlet temperature, Ti(t), up to a certain desired outlet temperature, T(t). As mentioned, the heating medium is condensing steam.The energy gained by the process fluid is equal to the heat released by the steam, provided there are no heat losses to surroundings, iii that is, the heat exchanger andpiping are well insulated.In this process there are many variables that can change, causing the outlet temperature to deviate from its desired value. [21 If this happens, some action must be taken to correct for this deviation. That is, the objective is to control the outlet process temperature to maintain its desired value.One way to accomplish this objective is by first measuring the temperature T(t) , then comparing it to its desired value, and, based on this comparison, deciding what to do to correct for any deviation. The flow of steam can be used to correct for the deviation. This is, if the temperature is above its desired value, then the steam valve can be throttled back to cut the stearr flow (energy) to the heat exchanger. If the temperature is below its desired value, then the steam valve could be opened some more to increase the steam flow (energy) to the exchanger. All of these can be done manually by the operator, and since the procedure is fairly straightforward, it should present no problem. However, since in most process plants there are hundreds of variables that must be maintained at some desired value, this correction procedure would required a tremendous number of operators. Consequently, we would like to accomplish this control automatically. That is, we want to have instnnnents that control the variables wJtbom requ)ring intervention from the operator. (si This is what we mean by automatic process control.To accomplish ~his objective a control system must be designed and implemented.A possible control system and its basic components are shown in Fig.2.Fig. 2 Heat exchanger control loopThe first thing to do is to measure the outlet temperaVare of the process stream. A sensor (thermocouple, thermistors, etc) does this. This sensor is connected physically to a transmitter, which takes the output from the sensor and converts it to a signal strong enough to be transmitter to a controller. The controller then receives the signal, which is related to the temperature, and compares it with desired value. Depending on this comparison, the controller decides what to do to maintain the temperature at its desired value. Base on this decision, the controller then sends another signal to final control element, which in turn manipulates the steam flow.The preceding paragraph presents the four basic components of all control systems. They are(1) sensor, also often called the primary element.(2) transmitter, also called the secondary element.(3) controller, the "brain" of the control system.(4) final control system, often a control valve but not always. Other common final control elements are variable speed pumps, conveyors, and electric motors.The importance of these components is that they perform the three basic operations that must be present in every control system. These operations are(1) Measurement (M) : Measuring the variable to be controlled is usually done bythe combination of sensor and transmitter.(2) Decision (D): Based on the measurement, the controller must then decide what to do to maintain the variable at its desired value.(3) Action (A): As a result of the controller's decision, the system must then take an action. This is usually accomplished by the final control element.As mentioned, these three operations, M, D, and A, must be present in every control system.PID controllers can be stand-alone controllers (also called single loop controllers), controllers in PLCs, embedded controllers, or software in Visual Basic or C# computer programs.PID controllers are process controllers with the following characteristics:Continuous process controlAnalog input (also known as "measuremem" or "Process Variable" or "PV")Analog output (referred to simply as "output")Setpoint (SP)Proportional (P), Integral (I), and/or Derivative (D) constantsExamples of "continuous process control" are temperature, pressure, flow, and level control. For example, controlling the heating of a tank. For simple control, you have two temperature limit sensors (one low and one high) and then switch the heater on when the low temperature limit sensor tums on and then mm the heater off when the temperature rises to the high temperature limit sensor. This is similar to most home air conditioning & heating thermostats.In contrast, the PID controller would receive input as the actual temperature and control a valve that regulates the flow of gas to the heater. The PID controller automatically finds the correct (constant) flow of gas to the heater that keeps the temperature steady at the setpoint. Instead of the temperature bouncing back and forth between two points, the temperature is held steady. If the setpoint is lowered, then the PID controller automatically reduces the amount of gas flowing to the heater. If the setpoint is raised, then the PID controller automatically increases the amount of gas flowing to the heater. Likewise the PID controller would automatically for hot, sunnydays (when it is hotter outside the heater) and for cold, cloudy days.The analog input (measurement) is called the "process variable" or "PV". You want the PV to be a highly accurate indication of the process parameter you are trying to control. For example, if you want to maintain a temperature of + or -- one degree then we typically strive for at least ten times that or one-tenth of a degree. If the analog input is a 12 bit analog input and the temperature range for the sensor is 0 to 400 degrees then our "theoretical" accuracy is calculated to be 400 degrees divided by 4,096 (12 bits) =0.09765625 degrees. [~] We say "theoretical" because it would assume there was no noise and error in our temperature sensor, wiring, and analog converter. There are other assumptions such as linearity, etc.. The point being--with 1/10 of a degree "theoretical" accuracy--even with the usual amount of noise and other problems-- one degree of accuracy should easily be attainable.The analog output is often simply referred to as "output". Often this is given as 0~100 percent. In this heating example, it would mean the valve is totally closed (0%) or totally open (100%).The setpoint (SP) is simply--what process value do you want. In this example--what temperature do you want the process at?The PID controller's job is to maintain the output at a level so that there is no difference (error) between the process variable (PV) and the setpoint (SP).In Fig. 3, the valve could be controlling the gas going to a heater, the chilling of a cooler, the pressure in a pipe, the flow through a pipe, the level in a tank, or any other process control system. What the PID controller is looking at is the difference (or "error") between the PV and the SP.P，I，&DDifference error PID controlprocessvariableFig .3 PIDcontrolIt looks at the absolute error and the rate of change of error. Absolute error means--is there a big difference in the PV and SP or a little difference? Rate of change of error means--is the difference between the PV or SP getting smaller or larger as time goes on.When there is a "process upset", meaning, when the process variable or the setpoint quickly changes--the PID controller has to quickly change the output to get the process variable back equal to the setpoint. If you have a walk-in cooler with a PID controller and someone opens the door and walks in, the temperature (process variable) could rise very quickly. Therefore the PID controller has to increase the cooling (output) to compensate for this rise in temperature.Once the PID controller has the process variable equal to the setpoint, a good PID controller will not vary the output. You want the output to be very steady (not changing) . If the valve (motor, or other control element) is constantly changing, instead of maintaining a constant value, this could cause more wear on the control element.So there are these two contradictory goals. Fast response (fast change in output) when there is a "process upset", but slow response (steady output) when the PV is close to the setpoint.Note that the output often goes past (over shoots) the steady-state output to get the process back to the setpoint. For example, a cooler may normally have its cooling valve open 34% to maintain zero degrees (after the cooler has been closed up and the temperature settled down). If someone opens the cooler, walks in, walks around to find something, then walks back out, and then closes the cooler door--the PID controller is freaking out because the temperature may have raised 20 degrees! So it may crank the cooling valve open to 50, 75, or even 100 percent--to hurry up and cool the cooler back down--before slowly closing the cooling valve back down to 34 percent.Let's think about how to design a PID controller.We focus on the difference (error) between the process variable (PV) and the setpoint (SP). There are three ways we can view the error.The absolute errorThis means how big is the difference between the PV and SP. If there is a small difference between the PV and the SP--then let's make a small change in the output. If there is a large difference in the PV and SP--then let's make a large change in the output. Absolute error is the "proportional" (P) component of the PID controller.The sum of errors over timeGive us a minute and we will show why simply looking at the absolute error (proportional) only is a problem. The sum of errors over time is important and is called the "integral" (I) component of the PID controller. Every time we run the PID algorithm we add the latest error to the sum of errors. In other words Sum of Errors = Error 1 q- Error2 + Error3 + Error4 + ....The dead timeDead time refers to the delay between making a change in the output and seeing the change reflected in the PV. The classical example is getting your oven at the right temperature. When you first mm on the heat, it takes a while for the oven to "heat up". This is the dead time. If you set an initial temperature, wait for the oven to reach the initial temperature, and then you determine that you set the wrong temperature--then it will take a while for the oven to reach the new temperature setpoint. This is also referred to as the "derivative" (D) component of the PID controller. This holds some future changes back because the changes in the output have been made but are not reflected in the process variable yet.Absolute Error/ProportionalOne of the first ideas people usually have about designing an automatic process controller is what we call "proportional". Meaning, if the difference between the PV and SP is small--then let's make a small correction to the output. If the difference between the PV and SP is large-- then let's make a larger correction to the output. Thisidea certainly makes sense.We simulated a proportional only controller in Microsoft Excel. Fig.4 is the chart showing the results of the first simulation (DEADTIME = 0, proportional only): Proportional and Integral ControllersThe integral portion of the PID controller accounts for the offset problem in a proportional only controller. We have another Excel spreadsheet that simulates a PID controller with proportional and integral control. Here (Fig. 5) is a chart of the first simulation with proportional and integral (DEADTIME :0, proportional = 0.4).As you can tell, the PI controller is much better than just the P controller. However, dead time of zero (as shown in the graph) is not common.Fig .4 The simulation chartDerivative ControlDerivative control takes into consideration that if you change the output, then it takes tim for that change to be reflected in the input (PV).For example, let's take heating of the oven.Fig.5The simulation chartIf we start turning up the gas flow, it will take time for the heat to be produced, the heat to flow around the oven, and for the temperature sensor to detect the increased heat. Derivative control sort of "holds back" the PID controller because some increase in temperature will occur without needing to increase the output further. Setting the derivative constant correctly allows you to become more aggressive with the P & Iconstants.2、外文资料翻译译文温度控制简介和PID控制器过程控制系统自动过程控制系统是指将被控量为温度、压力、流量、成份等类型的过程变量保持在理想的运行值的系统。

自动化专业英语原文和翻译

自动化专业英语原文和翻译引言概述：自动化是现代工程技术领域中的重要学科，它涉及到自动控制系统、机器人技术、传感器技术等多个领域。

在自动化专业中，学习和掌握英语是必不可少的，因为英语是国际通用语言，也是自动化领域中的重要交流工具。

本文将介绍一些常见的自动化专业英语原文和翻译，以帮助学习者更好地理解和运用这些术语。

一、自动化概念及应用1.1 自动化定义英文原文：Automation refers to the use of technology to control and operate processes or systems without human intervention.翻译：自动化是指利用技术来控制和操作过程或系统，无需人为干预。

1.2 自动化应用领域英文原文：Automation is widely applied in manufacturing, transportation, healthcare, and many other industries.翻译：自动化广泛应用于制造业、交通运输、医疗保健等许多行业。

1.3 自动化优势英文原文：Automation offers advantages such as increased productivity, improved efficiency, and enhanced safety.翻译：自动化提供了增加生产力、提高效率和增强安全性等优势。

二、自动控制系统2.1 自动控制系统定义英文原文：An automatic control system is a set of devices that manage and regulate the behavior of a system or process automatically.翻译：自动控制系统是一组设备，能够自动管理和调节系统或过程的行为。

2.2 自动控制系统组成英文原文：An automatic control system consists of sensors, actuators, controllers, and communication networks.翻译：自动控制系统由传感器、执行器、控制器和通信网络组成。

自动化专业毕业设计外文翻译1

外文资料Programmable Logic Controllers (PLC), a computing device invented by Richard E. Morley in 1968, have been widely used in industry including manufacturing systems, transportation systems, chemical process facilities, and many others. At that time, the PLC replaced the hardwired logic with soft-wired logic orso-called relay ladder logic (RLL), a programming language visually resembling the hardwired logic, and reduced thereby the configuration time from 6 months down to 6 days [Moody and Morley, 1999].Although PC based control has started to come into place, PLC based control will remain the technique to which the majority of industrial applications will adhere due to its higher performance, lower price, and superior reliability in harsh environments. Moreover, according to a study on the PLC market of Frost and Sullivan [1995], an increase of the annual sales volume to 15 million PLC per year with the hardware value of more than 8 billion US dollars has been predicted, though the prices of computing hardware is steadily dropping. The inventor of the PLC, Richard E Morley, fairly considers the PLC market as a 5-billion industry at the present time.Though PLCare widely used in industrial practice, the programming of PLC based control systems is still very much relying on trial-and-error. Alike software engineering, PLC software design is facing the software dilemma or crisis in a similar way. Morley himself emphasized this aspect most forcefully by indicating:“If houses were built like software projects, a single woodpecker could destroy civilization.”Particularly, practical problems in PLC programming are to eliminate software bugs and to reduce the maintenance costs of old ladder logic programs. Though the hardware costs of PLC are dropping continuously, reducing the scan time of the ladder logic is still an issue in industry so that low-cost PLC can be used.In general, the productivity in generating PLC is far behind compared to other domains, for instance, VLSI design, where efficient computer aided design tools are in practice. Existent software engineering methodologies are not necessarily applicable to the PLC based software design because PLC-programming requires a simultaneous consideration of hardware and software. The software design becomes, thereby, more and more the major cost driver. In many industrial design projects,more than SO0/a of the manpower allocated for the control system design and installation is scheduled for testing and debugging PLC programs [Rockwell, 1999].In addition, current PLC based control systems are not properly designed to support the growing demand for flexibility and reconfigurebility of manufacturing systems. A further problem, impelling the need for a systematic design methodology, is the increasing software complexity in large-scale projects.The objective of this thesis is to develop a systematic software design methodology for PLC operated automation systems. The design methodology involves high-level description based on state transition models that treat automation control systems as discrete event systems, a stepwise design process, and set of design rules providing guidance and measurements to achieve a successful design. The tangible outcome of this research is to find a way to reduce the uncertainty in managing the control software development process, that is, reducing programming and debugging time and their variation, increasing flexibility of the automation systems, and enabling software reusability through modularity. The goal is to overcome shortcomings of current programming strategies that are based on the experience of the individual software developer.A systematic approach to designing PLC software can overcome deficiencies in the traditional way of programming manufacturing control systems, and can have wide ramifications in several industrial applications. Automation control systems are modeled by formal languages or, equivalently, by state machines. Formal representations provide a high-level description of the behavior of the system to be controlled. State machines can be analytically evaluated as to whether or not they meet the desired goals. Secondly, a state machine description provides a structured representation to convey the logical requirements and constraints such as detailed safety rules. Thirdly, well-defined control systems design outcomes are conducive to automatic code generation- An ability to produce control software executable on commercial distinct logic controllers can reduce programming lead-time and labor cost. In particular, the thesis is relevant with respect to the following aspects.In modern manufacturing, systems are characterized by product and process innovation, become customer-driven and thus have to respond quickly to changing system requirements. A major challenge is therefore to provide enabling technologies that can economically reconfigure automation control systems in response to changing needs and new opportunities. Design and operational knowledge can be reused in real-time, therefore, giving a significant competitive edge in industrial practice.Studies have shown that programming methodologies in automation systems have not been able to match rapid increase in use of computing resources. For instance, the programming of PLC still relies on a conventional programming style with ladder logic diagrams. As a result, the delays and resources in programming are a major stumbling stone for the progress of manufacturing industry. Testing and debugging may consume over 50% of the manpower allocated for the PLC program design. Standards have been formed to fix and disseminate state-of-the-art design methods, but they normally cannot participate in advancing the knowledge of efficient program and system design.A systematic approach will increase the level of design automation through reusing existing software components, and will provide methods to make large-scale system design manageable. Likewise, it will improve software quality and reliability and will be relevant to systems high security standards, especially those having hazardous impact on the environment such as airport control, and public railroads.The software industry is regarded as a performance destructor and complexity generator. Steadily shrinking hardware prices spoils the need for software performance in terms of code optimization and efficiency. The result is that massive and less efficient software code on one hand outpaces the gains in hardware performance on the other hand. Secondly, software proliferates into complexity of unmanageable dimensions; software redesign and maintenance-essential in modern automation systems-becomes nearly impossible. Particularly, PLC programs have evolved from a couple lines of code 25 years ago to thousands of lines of code with a similar number of 1/O points. Increased safety, for instance new policies on fire protection, and the flexibility of modern automation systems add complexity to the program design process. Consequently, the life-cycle cost of software is a permanently growing fraction of the total cost. 80-90% of these costs are going into software maintenance, debugging, adaptation and expansion to meet changing needs中文翻译1968年，Richard E. Morley创造出了新一代工业控制装置可编程逻辑控制器(PLC),现在，PLC已经被广泛应用于工业领域，包括机械制造也、运输系统、化学过程设备、等许多其他领域。

自动化专业英语原文和翻译

自动化专业英语原文和翻译Automation in the Field of EngineeringIntroduction:Automation plays a crucial role in various industries, including engineering. It involves the use of technology and machinery to perform tasks with minimal human intervention. In this document, we will discuss the importance of automation in the field of engineering and its impact on various aspects of the industry. Additionally, we will provide an original English text followed by its translation in Chinese, focusing on the terminology used in the field of automation.Importance of Automation in Engineering:Automation has revolutionized the engineering industry by improving efficiency, accuracy, and productivity. It allows engineers to streamline processes and reduce the risk of errors. With the help of automation, engineers can focus on more complex tasks that require critical thinking and problem-solving skills.Automation in Manufacturing:In the manufacturing sector, automation has significantly transformed the production process. Machines and robots are used to perform repetitive tasks with precision and speed. This not only reduces human error but also increases the overall production capacity. Automation in manufacturing has led to improved quality control, reduced costs, and faster time-to-market for products.Automation in Design and Analysis:Automation has also made a significant impact on the design and analysis phase of engineering projects. Computer-aided design (CAD) software allows engineers to create and modify designs with ease. It enables them to visualize and simulate the performance of their designs, leading to better decision-making. Furthermore, automation in analysis,such as finite element analysis (FEA), helps engineers predict the behavior of structures and systems under different conditions, ensuring safety and reliability.Automation in Construction:The construction industry has also embraced automation to enhance efficiency and safety. Robotic systems are used for tasks such as bricklaying, concrete pouring, and welding. These systems can work continuously without fatigue and perform tasks with precision, reducing the risk of accidents. Additionally, automation in construction allows for better project management, improved resource utilization, and faster completion times.Automation in Maintenance and Monitoring:Automation has revolutionized the field of maintenance and monitoring in engineering. Sensors and monitoring systems are used to collect real-time data on the performance of machines and structures. This data is then analyzed using automation techniques to detect anomalies and predict failures. By implementing proactive maintenance strategies based on automation, engineers can prevent costly breakdowns, minimize downtime, and optimize the lifespan of assets.Automation Terminology - English and Chinese Translation:Original English Text:1. Programmable Logic Controller (PLC): A digital computer used for automation of electromechanical processes.2. Human-Machine Interface (HMI): A graphical user interface that allows operators to interact with automation systems.3. Supervisory Control and Data Acquisition (SCADA): A system used for remote monitoring and control of industrial processes.4. Distributed Control System (DCS): A control system used to manage and control complex processes in various industries.5. Internet of Things (IoT): The network of physical devices, vehicles, and other objects embedded with sensors, software, and connectivity.Chinese Translation:1. 可编程逻辑控制器（PLC）：用于电机电子过程自动化的数字计算机。

自动化专业毕业设计(论文)外文翻译-----电子动力转向系统

自动化专业毕业设计（论文）外文翻译Electronic power steering systemWhat it isElectrically powered steering uses an electric motor to drive either the power steering HYPERLINK "/infobank/epc.htm" \t "_top" hydraulic pump or the steering linkage directly. The power steering function is therefore independent of engine speed, resulting in significant energy savings.How it works :Conventional power HYPERLINK "/infobank/epc.htm" \t "_top" steering systems use an engine accessory belt to drive the pump, providing pressurized fluid that operates a piston in the power steering gear or actuator to assist the driver.In electro-hydraulic steering, one electrically powered steering concept uses a high efficiencypump driven by an HYPERLINK "/infobank/epc.htm" \t "_top" electric motor. Pump speed is regulated by an electric controller to vary pump pressure and flow, providing steering efforts tailored for different driving situations. The pump can be run at low speed or shut off to provide energy savings during straight ahead driving (which is most of the time in most world markets).Direct electric steering uses an electric motor attached to the HYPERLINK "/infobank/epc.htm" \t "_top" steering rack via a gear mechanism (no pump or fluid). A variety of motor types and gear drives is possible. A microprocessor controls steering dynamics and driver effort. Inputs include vehicle speed and steering, wheel torque, angular position and turning rate.Working In Detail:A "steering sensor" is located on the input shaft where it enters the gearbox housing. The steering sensor is actually two sensors in one: a "torque sensor" that converts steering torque input and its direction into voltage signals, and a "rotation sensor" that converts the rotation speed and direction into voltage signals. An "interface" circuit that shares the same housing converts the signals from the torque sensor and rotation sensor into signals the control electronics can process. Inputs from the steering sensor are digested by a microprocessor control unit that also monitors input from the vehicle's HYPERLINK "/infobank/epc.htm" \t "_top" speed sensor. The sensor inputs are then compared to determine how much power assist is required according to a preprogrammed "force map" in the control unit's memory. The control unit then sends out the appropriate command to the " HYPERLINK "/infobank/epc.htm" \t "_top" power unit" which then supplies the electric motor with current. The motor pushes the rack to the right or left depending on which way the voltage flows (reversing the current reverses the direction the motor spins). Increasing the current to the motor increases the amount of power assist.The system has three operating modes: a "normal" control mode in which left or right power assist is provided in response to input from the steering torque and rotationsensor's inputs; a "return" control mode which is used to assist steering return after completing a turn; and a "damper" control mode that changes with vehicle speed to improve road feel and dampen kickback.If the steering wheel is turned and held in the full-lock position and steering assist reaches a maximum, the control unit reduces current to the electric motor to prevent an overload situation that might damage the motor. The control unit is also designed to protect the motor against voltage surges from a faulty HYPERLINK "/infobank/epc.htm" \t "_top" alternator or charging problem. The electronic steering control unit is capable of self-diagnosing faults by monitoring the system's inputs and outputs, and the driving current of the electric motor. If a problem occurs, the control unit turns the system off by actuating a fail-safe relay in the power unit. This eliminates all power assist, causing the system to revert back to manual steering. A dash EPS warning light is also illuminated to alert the driver. To diagnose the problem, a technician jumps the terminals on the service check connector and reads out the HYPERLINK "/infobank/epc.htm" \t "_top" trouble codes. INCLUDEPICTURE "/infobank/images/eps-18-4.gif" \* MERGEFORMATINETHYPERLINK "/infobank/images/c01e.gif" click here to see a bigger HYPERLINK "/infobank/images/c01e.gif"INCLUDEPICTURE "/infobank/images/c01e.gif" \*MERGEFORMATINETElectric power steering systems promise weight reduction, fuel savings and package flexibility, at no cost penalty.Europe's high fuel prices and smaller vehicles make a fertile testbed for electric steering, a technology that promises automakers weight savings and fuel economy gains. And in a short time, electric steering will make it to the U.S., too. "It's just just a matter of time," says AlyBadawy, director of research and development for Delphi Saginaw Steering Systems in Saginaw, Mich. "The issue was cost and that's behind us now. By 2002 here in the U.S. the cost of electric power steering will absolutely be a wash over hydraulic." Today, electric and hybrid-powered vehicles (EV), including Toyota's Prius and GM's EV-1, are the perfect domain for electric steering. But by 2010, a TRW Inc. internal study estimates that one out of every three cars produced in the world will be equipped with some form of electrically-assisted steering. The Cleveland-based supplier claims its new steering systems could improve fuel economy by up to 2 mpg, while enhancing handling. There are true bottom-line benefits as well for automakers by reducing overall costs and decreasing assembly time, since there's no need for pumps, hoses and fluids. Another claimed advantage is shortened development time. For instance, a Delphi group developed E-TUNE, a ride-and-handling software package that can be run off a laptop computer. "They can take that computer and plug it in, attach it to the controller and change all the handling parameters -- effort level, returnability, damping -- on the fly," Badawy says. "It used to take months." Delphi has one OEM customer that should start low-volume production in '99. HYPERLINK "/adlog/c/r=12640&s=790604&o=13886:14023:13888:15399:&h=c n&p=&b=14&l=&site=23&pt=&nd=&pid=&cid=&pp=100&e=&rqid=01c17-ad-e8480771F615DF093&orh=LINE&oepartner=&epartner=&ppartner=&pdom=&cpnmod ule=&count=&ra=10.15.56.33&t=2008.04.19.09.09.02/http://cm/ck/9 998-57911-18316-1?mpt=2008.04.19.09.09.02" \t "_blank" Electric steering units are normally placed in one of three positions: column-drive, pinion-drive and rack-drive. Which system will become the norm is still unclear. Short term, OEMs will choose the steering system that is easiest to integrate into an existing platform. Obviously, greater potential comes from designing the system into an all-new platform. "We have all three designs under consideration," says Dr. Herman Strecker, group vice president of steering systems division at ZF in SchwaebischGmuend, Germany. "It's up to the market and OEMs which version finally will be used and manufactured." "The large manufacturers have all grabbed hold of what they consider a core technology," explains James Handy sides, TRW vice president, electrically assisted steering in Sterling Heights, Mich. His company offers a portfolio of electric steering systems (hybrid electric, rack-, pinion-, and column-drive). TRW originally concentrated on what it still believes is the purest engineering solution for electric steering--the rack-drive system. The system is sometimes refer to as direct drive or ball/nut drive. Still, this winter TRW hedged its bet, forming a joint venture with LucasVarity. The British supplier received $50 million in exchange for its electric column-drive steering technology and as sets. Initial production of the column and pinion drive electric steering systems is expected to begin in Birmingham, England, in 2000."What we lack is the credibility in the steering market," says Brendan Conner, managing director, TRW/LucasVarity Electric Steering Ltd. "The combination with TRW provides us with a good opportunity for us to bridge that gap." LucasVarity currently has experimental systems on 11 different vehicle types, mostly European. TRW is currently supplying its EAS systems for Ford and Chrysler EVs in North America and for GM's new Opel Astra.In 1995, according to Delphi, traditional hydraulic power steering systems were on 7596 of all vehicles sold globally. That 37-million vehicle pool consumes about 10 million gallons in hydraulic fluid that could be superfluous, if electric steering really takes off. The present invention relates to an electrically powered drive mechamsm for providing powered assistance to a vehicle steering mechanism. According to one aspect of the present invention, there is provided an electrically powered driven mechanism for providing powered assistance to a vehicle steering mechanism having a manually rotatable member for operating the steering mechanism, the drive mechanism including a torque sensor operable to sense torque being manually applied to the rotatable member, an electrically powered drive motor drivingly connected to the rotatable member and a controller which is arranged to control the speed and direction of rotation of the drive motor in response to signals received from the torque sensor, the torque sensor including a sensor shaft adapted for connection to the rotatable member to form an extension thereof so that torque is transmitted through said sensor shaft when the rotatable member is manually rotated and a strain gauge mounted on the sensor shaft for producing a signal indicative of the amount of torque being transmitted through said shaft. Preferably the sensor shaft is non-rotatably mounted at one axial end in a first coupling member and is non-rotatably mounted at its opposite axial end in a second coupling member, the first and second coupling members being inter-engaged to permit limited rotation there between so that torque under a predetermined limit is transmitted by the sensor shaft onlyand so that torque above said predetermined limit is transmitted through the first and second coupling members. The first and second coupling members are preferably arranged to act as a bridge for drivingly connecting first and second portions of the rotating member to one another. Preferably the sensor shaft is of generally rectangular cross-section throughout the majority of its length. Preferably the strain gauge includes one or more SAW resonators secured to the sensor shaft. Preferably the motor is drivingly connected to the rotatable member via a clutch .Preferably the motor includes a gear box and is concentrically arranged relative to the rotatable member. Various aspects of the present invention will hereafter be described, with reference to the accompanying drawings, in which :Figure 1 is a diagrammatic view of a vehicle steering mechanism including an electrically powered drive mechanism according to the present invention, Figure 2 is a flow diagram illustrating interaction between various components of the drive mechanism shown in Figure 1 ,Figure 3 is an axial section through the drive mechanism shown in Figure 1, Figure 4 is a sectional view taken along lines IV-IV in Figure 3,Figure 5 is a more detailed exploded view of the input drives coupling shown in Figure 3, and Figure 6 is a more detailed exploded view of the clutch showing in Figure 3. Referring initially to Figure 1 , there is shown a vehicle steering mechanism 10 drivingly connected to a pair of steerable road wheels The steering mechanism 10 shown includes a rack and pinion assembly 14 connected to the road wheels 12 via joints 15. The pinion(not shown) of assembly 14 is rotatably driven by a manually rotatable member in the form of a steering column 18 which is manually rotated by a steering wheel 19.The steering column 18 includes an electric powered drive mechanism 30 which includes an electric drive motor (not shown in Figure 1) for driving the pinion in response to torque loadings in the steering column 18 in order to provide power assistance for the operative when rotating the steering wheel 19.As schematically illustrated in Figure 2, the electric powered drive mechanism includes a torque sensor20 which measures the torque applied by the steering column 18 when driving the pinion and supplies a signal to a controller 40. The controller 40 is connected to a drive motor 50 and controls the electric current supplied to the motor 50 to control the amount of torque generated by the motor 50 and the direction of its rotation. The motor 50 is drivingly connected to the steering column 18 preferably via a gear box 60, preferably an epicyclic gear box, and a clutch 70. The clutch 70 is preferably permanently engaged during normal operation and is operative under certain conditions to isolate drive from the motor 50 to enable the pinion to be driven manually through the drive mechanism 30. This is a safety feature to enable the mechanism to function in the event of the motor 50 attempting to drive the steering column too fast and/or in the wrong direction or in the case where themotor and/or gear box have seized.The torque sensor 20 is preferably an assembly including a short sensor shaft on which is mounted a strain gauge capable of accurately measuring strain in the sensor shaft brought about by the application of torque within a predetermined range. Preferably the predetermined range of torque which is measured is 0-lONm; more preferably is about l-5Nm.Preferably the range of measured torque corresponds to about 0-1000 microstrain and the construction of the sensor shaft is chosen such that a torque of 5Nm will result in a twist of less than 2° in the shaft, more preferably less than 1 ° .Preferably the strain gauge is a SAW resonator, a suitable SAW resonator being described inWO91/13832. Preferably a configuration similar to that shown in Figure 3 of WO91/13832 is utilised wherein two SAW resonators are arranged at 45°to the shaft axis and at 90°to one another. Preferably the resonators operate with a resonance frequency of between 200-400 MHz and are arranged to produce a signal to the controller 40 of 1 MHz ± 500 KHz depending upon the direction of rotation of the sensor shaft. Thus, when the sensor shaft is not being twisted due to the absence of torque, it produces a 1 MHz signal. When the sensor shaft is twisted in one direction it produces a signal between 1.0 to 1.5 MHz. When the sensor shaft is twisted in the opposite direction it produces a signal between 1.0 to 0.5 MHz. Thus the same sensor is able to produce a signal indicative of the degree of torque and also the direction of rotation of the sensor shaft. Preferably the amount of torque generated by the motor in response to a measured torque of between 0-10Nm is 0-40Nm and for a measured torque of between l-5Nm is 0-25Nm.Preferably a feed back circuit is provided whereby the electric current being used by the motor is measured and compared by the controller 40 to ensure that the motor is running in the correct direction and providing the desired amount of power assistance. Preferably the controller acts to reduce the measured torque to zero and so controls the motor to increase its torque output to reduce the measured torque. A vehicle speed sensor (not shown) is preferably provided which sends a signal indicative of vehicle speed to the controller. The controller uses this signal to modify the degree of power assistance provided in response to the measured torque. Thus at low vehicle speeds maximum power assistance will be provided and a high vehicle speeds minimum power assistance will be provided。

机械设计制造及其自动化毕业论文中英文资料外文翻译

机械设计创造及其自动化毕业论文外文文献翻译INTEGRATION OF MACHINERY译文题目专业机械设计创造及其自动化外文资料翻译INTEGRATION OF MACHINERY（From ELECTRICAL AND MACHINERY INDUSTRY）ABSTRACTMachinery was the modern science and technology development inevitable result, this article has summarized the integration of machinery technology basic outline and the development background .Summarized the domestic and foreign integration of machinery technology present situation, has analyzed the integration of machinery technology trend of development.Key word： integration of machinery ，technology， present situation ，product t，echnique of manufacture ，trend of development0. Introduction modern science and technology unceasing development, impelled different discipline intersecting enormously with the seepage, has caused the project domain technological revolution and the transformation .In mechanical engineering domain, because the microelectronic technology and the computer technology rapid development and forms to the mechanical industry seepage the integration of machinery, caused the mechanical industry the technical structure, the product organization, the function and the constitution, the production method and the management systemof by machinery for the characteristic integration ofdevelopment phase.1. Integration of machinery outline integration of machinery is refers in the organization new owner function, the power function, in the information processing function and the control function introduces the electronic technology, unifies the system the mechanism and the computerization design and the software which constitutes always to call. The integration of machinery development also has become one to have until now own system new discipline, not only develops along with the science and technology, but also entrusts with the new content .But its basic characteristic may summarize is: The integration of machinery is embarks from the system viewpoint, synthesis community technologies and so on utilization mechanical technology, microelectronic technology, automatic control technology, computer technology, information technology, sensing observation and control technology, electric power electronic technology, connection technology, information conversion technology as well as software programming technology, according to the system function goal and the optimized organization goal, reasonable disposition and the layout various functions unit, in multi-purpose, high grade, redundant reliable, in the low energy consumption significance realize the specific function value, and causes the overall system optimization the systems engineering technology .From this produces functional system, then becomes an integration of machinery systematic or the integration of machinery product. Therefore, of coveringtechnology is based on the above community technology organic fusion one kind of comprehensive technology, but is not mechanical technical, the microelectronic technology as well as other new technical simple combination, pieces together .This is the integration of machinery and the machinery adds the machinery electrification which the electricity forms in the concept basic difference .The mechanical engineering technology has the merely technical to develop the machinery electrification, still was the traditional machinery, its main function still was replaces with the enlargement physical strength .But after develops the integration of machinery, micro electron installment besides may substitute for certain mechanical parts the original function, but also can entrust with many new functions,like the automatic detection, the automatic reduction information, demonstrate the record, the automatic control and the control automatic diagnosis and the protection automatically and so on .Not only namely the integration of machinery product is human's hand and body extending, human's sense organ and the brains look, has the intellectualized characteristic is the integration of machinery and the machinery electrification distinguishes in the function essence.2. Integration of machinery development condition integration of machinery development may divide into 3 stages roughly.20th century 60's before for the first stage, this stage is called the initial stage .In this time, the people determination not on own initiative uses the electronic technology the preliminary achievement to consummate the mechanical product the performance .Specially in Second World War period, the war has stimulated the mechanical product and the electronic technology union, these mechanical and electrical union military technology, postwar transfers civilly, to postwar economical restoration positive function .Developed and the development at that time generally speaking also is at the spontaneouscondition .Because at that time the electronic technology development not yet achieved certain level, mechanical technical and electronic technology union also not impossible widespread and thorough development, already developed the product was also unable to promote massively. The 20th century 70~80 ages for the second stage, may be called the vigorous development stage .This time, the computer technology, the control technology, the communication development, has laid the technology base for the integration of machinery development . Large-scale, ultra large scale integrated circuit and microcomputer swift and violent development, has provided the full material base for the integration of machinery development .This time characteristic is :①A mechatronics word first generally is accepted in Japan, probably obtains the quite widespread acknowledgment to 1980s last stages in the worldwide scale ;②The integration of machinery technology and the product obtained the enormous development ;③The various countries start to the integration of machinery technology and the product give the very big attention and the support. 1990s later periods, started the integration of machinery technology the new stagewhich makes great strides forward to the intellectualized direction, the integration of machinery enters the thorough development time .At the same time, optics, the communication and so on entered the integration of machinery, processes the technology also zhan to appear tiny in the integration of machinery the foot, appeared the light integration of machinery and the micro integration of machinery and so on the new branch; On the other hand to the integration of machinery system modeling design, the analysis and the integrated method, the integration of machinery discipline system and the trend of development has all conducted the thorough research .At the same time, because the hugeprogress which domains and so on artificial intelligence technology, neural network technology and optical fiber technology obtain, opened the development vast world for the integration of machinery technology .These research, will urge the integration of machinery further to establish the integrity the foundation and forms the integrity gradually the scientific system. Our country is only then starts from the beginning of 1980s in this aspect to study with the application .The State Councilsummary had considered fully on international the influence which and possibly brought from this about the integration of machinery technology developmenttrend .Many universities, colleges and institutes, the development facility and some large and middle scale enterprises have done the massive work to this technical development and the application, does not yield certain result, but and so on the advanced countries compared with Japan still has the suitable disparity.3. Integration of machinery trend of development integrations of machinery are the collection machinery, the electron, optics, the control, the computer, the information and so on the multi-disciplinary overlapping syntheses, its development and the progress rely on and promote the correlation technology development and the progress .Therefore, the integration of machinery main development direction is as follows:3.1 Intellectualized intellectualizations are 21st century integration of machinery technological development important development directions .Theartificial intelligence obtains day by day in the integration of machinery constructor's research takes, the robot and the numerical control engine bedis to the machine behavior description, is in the control theory foundation, the absorption artificial intelligence, the operations research, the computer science, the fuzzy mathematics, the psychology, the physiology and the chaos dynamics and so on the new thought, the new method, simulate the human intelligence, enable it to have abilities and so on judgment inference, logical thinking, independent decision-making, obtains the higher control goal in order to .Indeed, enable the integration of machinery product to have with the human identical intelligence, is not impossible, also is nonessential .But, the high performance, the high speed microprocessor enable the integration of machinery product to have preliminary intelligent or human's partial intelligences, then is completely possible and essential.In the modern manufacture process, the information has become the control manufacture industry the determining factor, moreover is the most active actuation factor .Enhances the manufacture system information-handling capacity to become the modern manufacture science development a key point .As a result of the manufacture system information organization and structure multi-level, makes the information the gain, the integration and the fusion presents draws up the character, information measure multi-dimensional, as well as information organization's multi-level .In the manufacture information structural model, manufacture information uniform restraint, dissemination processing and magnanimous data aspects and so on manufacture knowledge library management, all also wait for further break through.Each kind of artificial intelligence tool and the computation intelligence method promoted the manufacture intelligence development in the manufacture widespread application .A kind based on the biological evolution algorithm computation intelligent agent, in includes thescheduling problem in the combination optimization solution area of technology, receives the more and more universal attention, hopefully completes the combination optimization question when the manufacture the solution speed and the solution precision aspect breaks through the question scale in pairs the restriction .The manufacture intelligence also displays in: The intelligent dispatch, the intelligent design, the intelligent processing, the robot study, the intelligent control, the intelligent craft plan, the intelligent diagnosis and so on are various These question key breakthrough, may form the product innovation the basic research system. Between 2 modern mechanical engineering front science different science overlapping fusion will have the new science accumulation, the economical development and society's progress has had the new request and the expectation to the science and technology, thus will form the front science .The front science also has solved and between the solution scientific question border area .The front science has the obvious time domain, the domain and the dynamic characteristic .The project front science distinguished in the general basic science important characteristic is it has covered the key science and technology question which the project actual appeared.Manufacture system is a complex large-scale system, for satisfies the manufacture system agility, the fast response and fast reorganization ability, must profit from the information science, the life sciences and the social sciences and so on the multi-disciplinary research results, the exploration manufacture system new architecture, the manufacture pattern and the manufacture system effective operational mechanism .Makes the system optimization the organizational structure and the good movement condition is makes the system modeling , the simulation and the optimized essential target .Not only the manufacture system new architecture to makes the enterprise the agility and may reorganize ability to the demand response ability to have the vital significance, moreover to made the enterprise first floor production equipment the flexibility and may dynamic reorganization ability set a higher request .The biological manufacture view more and more many is introduced the manufacture system, satisfies the manufacture system new request.The study organizes and circulates method and technique of complicated system from the biological phenomenon, is a valid exit which will solve many hard nut to cracks that manufacturing industry face from now on currently .Imitating to living what manufacturing point is mimicry living creature organ of from the organization, from match more, from growth with from evolution etc. function structure and circulate mode of a kind of manufacturing system and manufacturing process.The manufacturing drives in the mechanism under, continuously by one's own perfect raise on organizing structure and circulating mode and thus to adapt the process of[with] ability for the environment .For from descend but the last product proceed together a design and make a craft rules the auto of the distance born, produce system of dynamic state reorganization and product and manufacturing the system tend automatically excellent provided theories foundation and carry out acondition .Imitate to living a manufacturing to belong to manufacturing science and life science of"the far good luck is miscellaneous to hand over", it will produce to the manufacturing industry for 21 centuries huge of influence .机电一体化摘要机电一体化是现代科学技术发展的必然结果,本文简述了机电一体化技术的基本概要和发展背景。

自动化专业毕业设计外文翻译--输入力矩受限的机器人鲁棒自适应控制

外文文献原文Limited torque input Robust Adaptive Tracking Control ofRobotAbstractBased on input constraints, a novel robust-adaptive tracking control algorithm is proposed for robot manipulators since stability if the standard adaptive control system is problematic when some disturbance exists. The proposed controller stabilizes the system with some disturbance and guarantees asymptotic stability in the case if non-disturbance. Robust-adaptive algorithm can be received as the extension of the conventional adaptive scheme. The estimated parameters enter the controller non-linearly and the resulting closed-loop system. The algorithm provides further flexibility fir adaptive controller design and better transient performance and robustness to disturbance and error of estimated parameter-region especially. Simulation results demonstrate it effectiveness.Keywords: Adaptive control; robot manipulator; parametric uncertainties; robust-adaptive;So far, almost all of the controller design is based on joint drive to produceany torque on the basis of; and is subject to the physical conditions, the output of the drive torque is limited, so the controller may lead to the control failure or deterioration of the quality control.Therefore the controller design must take into account the limited joint drive dynamic capability.For example, the operation of the industry to help the robot, some parameters are uncertain or unknown, adaptive control is based on the estimated parameters to deal with such issues one of the main control strategy, using the robot dynamic equations of linear parametric nature, through an integral operator estimates the robot parameters. As integral part of the role in the continued interference conditions, stability control system is not easy, so appropriate to limit or adjust the integral part of the role of the adaptive system to achieve an effective means of stabilization. Son ah estimated parameters can limit the extent required, thereby increasing the robustness of adaptive control system. However, this algorithm has six switch component, a little complicated, but really is the parameter is not specified range, it cannot give the system control quality and robustness of information.This paper presents a simple robust adaptive control algorithm, when the estimated parameters field contains the parameters of the true value, the closed-loop system to achieve asymptotically stable tracking; when there is interference or the estimated parameters with the true value of free parameter that is when the error system is stable.1. MANIPULATOR DYNAMIC MODEL AND CHARACTERISTIC MODELConsider a robotic manipulator with n degrees of freedom. The continuous Lagrange dynamic model is given by()(,)()M q q C q q q G q u ++= Where q ∈R n and q ∈R nare the vector of generalized joint coordinates and velocity coordinates, respectively. The inertia matrix M(q)-M T (q)> 0 ，and there exist two constant positive scalars M min and M max such that minM ≤M ≤max M , nu R ∈is the vector of commanded generalized force, and (,)C q qq andG(q) are the terms due to Carioles, Centripetal and gravity forces. In actual application, the uncertain parameters and un-modeled dynamics usually exist in the established dynamic model in (1).When the sample time sT is small enough, at instant t=k s T q and q can be approximated by()(1)s q k q k q T --≈ and 2(1)2()(1)s q k q k q k qT +-+-≈ . Respectively Using the above relationships thediscrete-time representation of (1) becomes ()()()()()()()()()()12211S M q k q k f k q k f k q k G k u k T '∙+--+=(2a) Premultiplying(2a) by ()()21sT mM q k -results in()()()()()()()()1211q k f k q k f k q k G k k u k β'+---+- where()()()()()()112,s f k I T M q k C q k qk -=- , ()()()()()()12,s f k I T M q k C q k qk -=-+ ()()()()()()()()2121s s G k T M q k G q k k T Mq k β--'==and I denotes the unitary diagonal matrix with an appropriate dimension.If the designed (),,u t q q (),,u t q q is continuous in t ,q and q , then the solution (q,q ) of (1) will be continuously differentiable. Let()()()1,,W q qM q C q q -= and (),ij w q q be ij-th element of matrix (),ij W q q ; We define()()()()11111SF k f k f k T =--and then ΔF1(k) can be expressed as()()()()()()()1,1,1F k W q k qk W q k q k =--- For the ij-th element Δf1,ij(k) of matrix ΔF1(k)we can get()()()()()()()()1,,1,1ij ij ij f k w q k qk w q k q k =---- =()()()()()()()1111,|1ij q q k T qq k w q qq k q k q ςς=-=-∂---∂()()()()()()()1111,|1ij q q k T qq k w q qq k q k q ςς=-=-∂---∂ =()()()()()11211,|1ij s q q k T qq k w q q T q k q ςςς=-=-∂--∂ ()()()()()11311,|1ij s q q k T qq k w q qT q k q ςςς=-=-∂--∂with 0≤1ς≤1,and 2ς,3ς≈1 for a small sample time Ts . From (3), it can beseen that ΔF1(k)→0 as Ts converges to zero in a compact set of (),q q(),q q.Similar properties can also be achieved for the coefficient matrixes f2(k),()G k '()G k ' and β (k) .In a compact set of (),q q, the following properties can be deduced from (3)and the expressions of the coefficient matrixes of (2b):Property 1: If the sample time Ts is small enough,then all coefficient matrixes of (2b) are slowly time varying;Property 2: f1(k)→2I,f2(k)→ −I and f1(k)+f2(k)→I, as the sample time Ts converges to zero. Then we can define the discrete equation (2b) with Properties 1 and 2 as the robotic manipulator characteristic model.2. MULTI-VARIABLE GSA CONTROLLER WITH NN COMPENSATIONDiscrete equation (2b) can be expressed as follows:()()()()1T q k k k e k θφ+=+()()()()1T q k k k e k θφ+=+ (4) Where()()()()()12,,,Tk f k f k k G k θβ'=⎡⎤⎣⎦,()()()(),1,,1TT T T Tk q k q k u k φ⎡⎤=--⎣⎦,e(k) denotes the vector of white noise with zero mean. In the case of ()G k ' ≡0, ()k θand ()k φ can be reduced to()()()()12,,Tk f k f k k θβ=⎡⎤⎣⎦()()()(),1,,TT T Tk q k q k u k φ⎡⎤=-⎣⎦Then the elements of q(k +1) can be expressed as()()()()1i i j q k k k e k φθ+=+ (5)wherei = 1,…,n, i q (k+1)) is the element i of q(k +1), ()i e k is the element i of e(k) and ()i k θ is the column i of the matrix()()()()()()()()()()()11111T T TP k k k P k p k k p k k k P k k φφλλφφ-⎡⎤--=∙--⎢⎥+-⎢⎥⎣⎦()k Θ . When the coefficient matrixes are unknown, it can be estimated by()ˆk Θ=π (q(k),q(k−1),...,u(k−1),...) , (6a) where ()ˆk Θis the estimated coefficie nt matrix of Θ(k) at the instant t=kTs , and ()π∙ denotes an estimation operator. Considering the coefficient matrixesof the characteristic model being slowly time-varying, we can obtain the selected estimation operator by the weighted least squares method (WLS)[13], namely()()()()()()()()()()()()1ˆ111i i i i TP k k k k q k k k k k P k k φθθφθλφφ-+=+∙+-+-, ()()()()()()()()()()()11111T T TP k k k P k p k k p k k k P k k φφλλφφ-⎡⎤--=∙--⎢⎥+-⎣⎦with λ(k+1)=μ0λ(k)+(1−μ0), 0<μ0 ≤1, and ()ˆik θ the column i of the matrix ()ˆk Θ. Given a desired smooth trajectory ()d q t , the adaptive control controller is designed as follows()()()()T G c u k u k u k u k =++ (7)with the feed forward control law designedas()()()()()()()()()()112ˆˆˆ11T d d du k k k I q k f k q k f k q k βε-=+∙+---(7a) and the multi-variable GSAC feedback law as()()()()()()()()()()11122ˆˆˆˆ1Gdu k k k I L fk q k L f k q k G k βε-'=+∙--+ (7b)where ()()()d qk q k q k =- is the tracking error andε(k) >0 is a small scalar that avoids the estimated matrix ()ˆk β being singular. The term of ()cu k will be designed later; L1 and L2 are golden-section coefficients, that is,210.6182L =≈130.3822L =≈, 210.6182L =≈,which satisfy the relationship L1+L2=1 and 212L L = Substituting (7) into (2), we can get()()()()()()()()22112111s c M q k q k L f qk L f q k k T u k +---=- (8)()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()11121222122122ˆˆˆ11d s c k M q k M k q k M q k f M k f k L q k L q k M q k s k M q k L f k s k M q k L I f k f k q k k T u k M q k L f k s k =-+--++=----+-=- ()()()()()()()()()()()()()()()2212ˆˆˆˆ11d M q k f M k f k L q k L q k M q k G k M k G q k ---+-+-and ()()()()12ˆˆsM k T k k I βε-=+.Defining the tracking filtered error s(k +1) as and using the relationships L1+L2=1 and 212L L =,212L L = (8) can be expressed as()()()()()()()()()()()()()222121M q k s k M q k L f k s k M q k L I f k f k qk +=---- ()()21s c k T u k +- =()()()()22M q k L f k s k - (9)()()()()()()()()2212ˆˆˆs c M q k L I f k f k q k k T u k +--+- Which()()()()()()()()1212k k M q k L I f k f k qk =--- ()()()()()()212ˆˆˆM q k L I f k f k q k +-- Assuming ,()()()ˆM k M q k =,()()()()()11ˆˆM k f k M q k f k = and ()()()()()22ˆˆM k f k M q k f k =,if ()c u k is selected as ()()()()()()()2212ˆˆˆc s u k T M q k L I f k f k q k -=-- then Δ(k) = 0 , and then (9) can be written as()()()221s k L f k s k +=-()()()221s k L f k s k +=- (10)Since in Property 2 ()2f k I →-()2f k I →-as Ts → 0 in a compact set of (),q q(),q q , a small sample time Ts can be selected such that the inequality ()221L f k < can be satisfied. Therefore, the tracking filtered error s(k)asymptotically converges to zero in this case. The convergence of s(k) to zero in turn guarantees the convergence of q(k) to zero. Because of the dynamics of the estimator and the time-varying coefficients of the characteristic model, it is almost impossible to satisfy the above assumptions. Therefore, we can design a suitable compensation control law ()c u k to avoid possibly the case that the control performance is deteriorated or that the close loop system is even unstable due to the estimation errors. Hence ()c u k is designed as()()()()()()()()()()()2212ˆˆˆc s i i i u k T M k L I f k f k q k k k Ty k k ψδ-=--+=+()()()111s k q k L q k +=+-()()()()()()()()2212ˆˆˆc s u k T M k L I f k f k q k k -=--+ (11) where ()ˆkis the estimate of Δ(k) . Assuming Δ(k) is smooth enough and bounded, it then can be approximated by the linearly parameterized NN to any required degree of accuracy [6,14]. Then the element Δi(k) of Δ(k) can be expressed as()()()i i i k Ty k k ψδ=+ (12)where i= 1,…n, T n i R ψψ∈ is the column i of the optimal NN weightmatrix,1T n ψψψψ⎡⎤=⎣⎦…,.Activation functions ()()(),,Tn y k y k y k ψ⎡⎤=⎣⎦… represent the basis function vector, which can be selected as any one of Gaussian radial basis, B-spine basis, Wavelet basis, and etc. [14], and δi (k) denotes the element I of the NN reconstruction error vectork δ(k), namely()()()1,T n k k k δδδ=⎡⎤⎣⎦…, .Using compensation control law ()c u k , (9) can be written as ()()()()()()()221M q k s k M q k L f k s k +=-()()11ˆˆ,Tn n y k k ψψψψψψδ⎡⎤+--+⎣⎦… (13) Where ()ˆi k ψis the estimate of i ψ, and ()max sup i kk ψδδ=<∞ An estimate ()ˆi k ψis now obtained by minimizing the cost function ()()()()1112T J s k M q k s k =++ (14)After substituting (13) into (14), the gradient of the cost function in (14) is derived as()()1ˆT Jy k s k ψ∂=-+∂ (15) According to the gradient descent method the NN weight adaptation law can be designed as()()()()ˆˆ11T k k y k s k ψψα+=++ (16) with α > 0 . Then the compensation control law ()c u k in (11) can bewritten as()()()()()()()()2122211ˆˆTc s su k M k L I f k f k qk k y k T T ψ=--+ (17) In view of the case ()()12ˆˆ0I fk f k --≈ the term ()cu k can be simplified as()()()21ˆTc su k k y k T ψ=4. SIMULATION RESULTSConsider a planar, two-link, articulated manipulator as in [3] (as presented in Fig. 1), whose dynamics can be written explicitly as()1112111212212222210M M qq u hq h q q M M q q u hq --+⎛⎫⎛⎫⎛⎫⎛⎫⎛⎫+= ⎪ ⎪⎪ ⎪ ⎪⎝⎭⎝⎭⎝⎭⎝⎭⎝⎭Where122123242cos sin M M a a q a q ==++ 11132322cos 2sin M a a q a q =++ 222M a =3242sin cos h a q a q =-With 22211111c e e ce e a I m l I m l m l =++++,22e e ce a I m l =+31cos e ce e a m l l δ=,41sin e ce e a m l l δ=,111,1,2,30,e e m l m δ==== 110.12,0.5,0.25,c e I I I ===and 0.6ce l =. In the simulation, the sample time Ts = 2ms, the initial values and the parameters of the estimator and the controller are selected as P(0) =1×310I,λ(0) = 0.96 , μ0 = 0.98 , the anti -singularity factors(k) can be designed as ε(k) =5×610-exp(−kTs).According to the Property 2, the initial estimate values of the characteristicmodel coefficient matrixes are chosen as ()()12ˆˆ02,0f I f I ==-A basis set of activation function y(k) can be selected as in the Random Vector Function Link net [16], namely,()()()T y k V X k σ= (19) with V a randomly selected matrix and X(k) the NN input vector. ()σ∙can be chosen as the h yperbolic tangent function, and X(k) can be taken as()()()()(),1,,,1TT T T Td d X k q k q k q k q k ⎡⎤=-⎣⎦.The adaptation gain for the NN weight tuning is taken as α = 0.005 , and the initial values of the weights are set to zeros.The desired trajectory is chosen as()()()301cos 2,451cos 2T d q t t t ππ⎡⎤=--⎣⎦(20)外文翻译输入力矩受限的机器人鲁棒自适应控制摘要在输入力矩受限的情况下，提出一种全的简单鲁棒自适应控制算法。

自动化专业毕业设计外文翻译--使用连续小波变换在配电系统中故障定位(中文)

中文6710字毕业设计（论文）外文翻译On the use of continuous-wavelet transform for fault location in distributiong power systems使用连续小波变换在配电系统中故障定位出处：International Journal of Electrical Power & Energy Systems, 2006, 28(9): 608-617使用连续小波变换在配电系统中故障定位a a a ab a R L M A C S A 蒂纳雷利布莱特保罗努奇科希博尔盖蒂.,.,.,..,.,.,*a 意大利波洛尼亚viale Risorgimento 2，40136波洛尼亚大学电气工程系，b 意大利米兰 CESI收于2006年3月31日;接受2006年3月31日摘要该论文说明了连续小波变换（CWT ）为分析由于线路故障引起电压瞬变得基本步骤并讨论了其应用于配电系统故障定位。

所进行的分析实现在网络中显示存在相关典型频率的连续小波变换转换信号和特殊路径代替转换小波引起的故障。

本文提出了一种在MV 离散系统中利用以上所提到的相关性确定MV 配电系统故障定位的步骤。

在本文中分析MV 离散系统是准确地以EMPT 模型为代表，以及研究各种故障类型和网络特点。

本文介绍了一些也基本测量概念和故障定位标准系统的分布式结构。

关键词：故障测距;配电系统;连续小波变换;电磁暂态;分布式测控系统1. 导言近年来中压配电网络的故障定位是一个日益受到重视研究话题，由于既要最严的质量的要求并要提供改进测量和监测系统。

此外，在网络需检修的传统程序的基础上增加的安装分布式发电资源自动开关系统。

最有前途的解决这个大家关注问题的方法似乎是在离散系统中运用适当的信号处理技术引起电压/电流瞬变产生的短路事件并记录在一个或更多的位置。

自动化专业英语原文和翻译

自动化专业英语原文和翻译自动化专业英语原文和翻译是指将自动化专业相关的文本内容进行英文原文和翻译的处理。

自动化专业是现代工程技术领域的一个重要学科，涉及到自动控制、机械电子、计算机科学等多个方面的知识。

在国际交流和学术研究中，使用英语进行交流和发表论文是非常普遍的。

下面是一段关于自动化专业的英文原文和翻译示例：原文：Automation is the technology by which a process or procedure is performed with minimal human assistance. It plays a crucial role in various industries, including manufacturing, transportation, and healthcare. Automation systems are designed to increase efficiency, improve safety, and reduce human errors. With the rapid development of technology, automation has become an essential part of modern society.翻译：自动化是一种通过最小化人类干预来执行过程或者程序的技术。

它在包括创造业、交通运输和医疗保健等各个行业中起着至关重要的作用。

自动化系统旨在提高效率、改善安全性并减少人为错误。

随着技术的快速发展，自动化已成为现代社会不可或者缺的一部份。

原文：In the field of automation, there are various sub-disciplines, such as industrial automation, process automation, and home automation. Industrial automation focuses on the use of control systems to operate industrial machinery and processes. Process automation involves the use of technology to automate repetitive tasks and streamline workflows. Home automation aims to provide convenience and comfort by integrating various household devices and systems.翻译：在自动化领域中，有各种子学科，如工业自动化、过程自动化和家庭自动化。

自动化专业毕业设计--中英文翻译

中英文翻译Classification of control systems there are three ways: by automatic classification methods in order to participate in the control mode classification, to adjust the law category.One way to control category 1, the open-loop control system if the computer output of open loop control system to exercise control of the production process, but the control results --- the state of the production process does not affect the computer control systems, computer \ controller \ production and other sectors does not constitute a closed loop, is called open-loop control system computer. the production process of the state is no feedback to the computer, but by the operator to monitor the status of the production process, decision control program, and tell the computer to control the role of exercising control. 2, closed loop control system computer to the production of an object or process control, the state can directly influence the production process computer control system, called the closed-loop control system computer. Control of the computer monitor in the operator, the automatic acceptance of the production process state test results, calculate and determine the control scheme, the direct command and control units (devices) of action, the role of exercising control of the production process. In such systems, aircraft control components under control of control information sent to control device operation, the other running equipment condition as the output, measured by the detection part, the feedback as input to the control computer; to make control Computer \ Control Components \ production \ test components form a closed loop. We will call this form of control computer control closed-loop control. Closed loop control system computer, using a mathematical model to set the value of the production process and test results of the best value of the deviation between the feedback and control the production process to run at their best. 3, line control system as long as the computer controlled production of the controlled object or process, to exercise direct control, without human intervention are called the control computer on-line control, or on-line control system. 4, offline control system control computer does not directly participate in the control object or the controlled production process. It only managed to complete the process of the controlled object or the status of testing, and testing of data processing; and then develop control programs, the output control instruction, operator reference control instructions manually controlled operation to control parts of the object or subject control process control. This control form is called off-line computer control system. 5, real-time control system control computer real-time control system iscontrolled by the control of the object or process, or request when the request processing control, the control function in a timely manner to address and control systems, commonly used in the production process is interrupted for the occasion. Such as steel, each one refining furnace steel is a process; and if the process rolling, rolling out each piece of steel considered a process, each process is repeated. Only enter the process only requires a computer control. Once control of the computer, it requires a computer from the production process information in the required time to respond to or control. Such systems often use sophisticated interrupt system and interrupt handling procedures to achieve. In summary, an online system is not necessarily a real-time system. But a real-time system must be an online system.Second, in order to participate in the control mode to Category 1, direct digital control system by the control computer to replace conventional analog instruments and direct regulation to control the production process, as the computer as digital signals, so named after the DDC control. Actually controlled the production process control components, control signals received by the process controller input / output channels of D / (D / A) converter output of the digital control computer volume to be converted into analog; analog input control machine to go through the process of input / output channels of analog / digital (A / D) converter into a digital number into the computer. DDC control systems often use a small computer or microprocessor, the time-sharing system to achieve multiple points of control. Is in fact a discrete sampling with the controller, to achieve discrete multi-point control. DDC computer control system that has become the main control computer control system forms. DDC control of the advantage of flexibility, large, focused on high reliability and low cost. Can use several forms of digital computing circuits, or even dozens of loop production process, integral to proportional --- --- differential (PID) control to maintain the industrial state of the controlled object at a given value, the deviation small and stable. And as long as the change of control algorithms and applications can achieve more complex control. Such as feedforward control and the best control. Under normal circumstances, DDC-level control often more complex as the implementation of advanced control level. 2, supervisory computer control system supervisory computer control system for a particular production process, according to the production process of various states, according to the production process of the mathematical model to calculate the best production equipment should be running a given value, and the best value automatically or manually on the DDCExecutive-level computer or analog meter to align the regulation or control of the target set. By a DDC or adjust the instrument at various points on the production process (running equipment) to exercise control. SCC system is that it can guarantee the production process is always controlled the situation in the best condition to run, so get the most benefit. SCC results directly affect the merits of the first of its mathematical model, this should always improve the operation process model, and modify the control algorithm, and application control procedures. 3, multi-level control systems in modern manufacturing enterprises in the production process not only the need to address the problem of online control, and Huan Zhi Li called for a solution of production problems, the daily product line, the number of arrangements for planning and scheduling, and Rose plans develop a long term planning, notice Xiaoshou prospects, there was multi-level control system. DDC class is mainly used for direct control of the production process, for PID, or feedforward control; SCC level is mainly used for optimal control or adaptive control or learning control calculation, and command and control the same DDC class report back to the MIS class. DDC level usually microcomputers, SCC-level general use of small computers or high-end microcomputers. MIS Workshop main function of governance is based on plant-level production of varieties issued, the number of orders and collect up the production process of the state of information, at any time reasonable schedule to achieve optimal control, command and SCC-level supervisory control. Factory management level MIS main function is to accept the company and factory production tasks assigned by the actual situation of optimized computing, Zhi Ding factory production plans and short-term (ten days or weeks or days) arrangements, and then issued to the plant-level production tasks. Corporate governance level MIS main function is to guess the market demand computing to develop strategic long-term development planning, and contract orders, raw material supply situation and the production conditions, comparison of the optimal production program selection and calculation, work out the entire company business a long time (months or ten days) of the production plan, sales plan, assigned to the task of the factory management level. MIS-level main function is to achieve real-time information processing, decision-makers at all levels to provide useful information, make on the production planning \ scheduling and management programs to plan the coordination and management control in the optimal state. This one can control the size and scope of enterprise size divided into several levels. Each level has to be addressed accordingto the size of the amount of information to determine the type of computer used. MIS generally use small computer shop class or high-grade micro-computer, the factory management level of the MIS with a medium-sized computer, and corporate governance level MIS is to use large-scale computer, or use super computer. 4, distributed control or distributed control system distributed control or distributed control, the control system is divided into a number of independent local control subsystems to complete the controlled production process control task. Since the emergence of micro-computers and rapid development of distributed control to provide for the realization of the material and technical basis, in recent years, decentralized control can be different almost normal development, and has become an important trend in the development of computer control. Since the 70's, appeared focused on distributed control system, called DCS. It is a decentralized local control of the new computer control system.Three, classified according to the law regulating 1, program control if the computer control system the division of a predetermined time function control, such control is called program control. Such as the furnace temperature-time curves Anzhao some control on the process control. Here the procedure is time-varying changes have to determine the corresponding value, rather than the computer running. 2, sequence control in the process control based on the generated sequence control, computer, over time, as can be determined according to the corresponding control value and previous results at the moment both to exercise on the production process control system, called the order of the computer control . 3, proportional - integral - differential analog PID control regulation of conventional PID control instrument can be completed. Micro-computer can also be achieved with PID control. 4, feedforward control is usually the feedback control system, have certain effects on the interference in order to generate feedback over the role of inhibitory control of interference, and thus delay the control of undesirable consequences. In order to overcome the negative lag control, with the computer accepts the interference signal after the, did not produce effects in the Huan insert a feedforward control Zuoyong, it Ganghao interference point in the interference of the control to completely offset the effect on the variable, it was Ming Wei Yin Er disturbance compensation control. 5, optimal control (optimal control) system control computer, such as to have controlled object is best known as the best run of the control system control system. Such as computer control system is limited in the existing conditions, select appropriate control law(mathematical model), the controlled object indicators in optimal running condition. Such as the largest output, consumption of the largest, highest quality standards, such as the least scrap rate. Best is determined by a set of mathematical models, sometimes several in a limited range of the best indicators of the pursuit of individual, sometimes the best indicators of comprehensive requirements. 6, the adaptive control system, optimal control, when the working conditions or qualifications change, we can not get the best control effects. If the situation changes in working conditions, the control system can still be controlled in the best state of the object's control, such control system called the adaptive system. This requires mathematical model reflects the change in the conditions, how to achieve the best state. Control computer to detect changes in terms of the information given by the laws of mathematical models to calculate, to change the control variables, the controlled objects still in the best condition. 7, self-learning control system if the computer can keep the results under the controlled object gain experience running their own change and improve the control law so that more and better control effect, this control system is called self-learning control system. Above mentioned optimal control, adaptive control and self-learning control are related to multi-parameter, multi-variable complex control systems, are all problems of modern control theory. Determine the stability of the system, many factors affect the control of complex mathematical models, have to be a production control, production technology, automation, instrumentation, programming, computer hardware, each with various personnel to be realized. Controlled object by the length of reaction time required to control the number of points and mathematical models to determine the complexity of the computer use scale. Generally speaking, a strong need to functionality (speed and computing power) of the computer can be achieved. The Zhuzhong control, can be a single type also is not single, you can combine several forms to achieve control of the production process. This should address the actual situation of the controlled object, the system analysis, system design determined at the time.Keywords ：open the control,closed loop control控制系统的分类有三种方法：以自动控制方式分类、以参于控制方式分类、以调节规律分类。

自动化专业英语原文和翻译

自动化专业英语原文和翻译英文原文：Automation is the technology by which a process or procedure is performed with minimal human assistance. Automation or automatic control is the use of various control systems for operating equipment such as machinery, processes in factories, boilers, and heat treating ovens, switching on telephone networks, steering, and stabilization of ships, aircraft, and other applications and vehicles with minimal or reduced human intervention. Some processes have been completely automated.自动化是一种通过至少的人力辅助来执行过程或者程序的技术。

自动化或者自动控制是使用各种控制系统来操作设备，例如机械、工厂中的工艺流程、锅炉和热处理炉、电话网络的开关、船舶、飞机和其他应用和车辆的控制和稳定，从而实现最小化或者减少人类干预。

一些过程已经彻底自动化。

Automation plays a crucial role in various industries and sectors, including manufacturing, transportation, healthcare, and many others. It involves the use of advanced technologies and control systems to streamline processes, improve efficiency, and reduce human error.In the manufacturing industry, automation is used extensively to carry out repetitive tasks, such as assembly line operations. This not only speeds up production but also ensures consistent quality and reduces the risk of accidents. Robots and robotic systems are commonly employed in manufacturing plants to handle tasks that are dangerous or require high precision.在创造业中，自动化被广泛应用于执行重复性任务，例如流水线操作。

自动化专业 毕业 外文翻译

自动化专业毕业论文外文文献翻译

电气工程与自动化毕业论文中英文资料外文翻译

自动化毕业设计英文翻译

自动化专业毕业设计外文翻译--现地控制单元在水电厂自动化中的应用

电气工程及其自动化专业毕业论文外文翻译

自动化专业外文翻译----温度控制简介和PID控制器

自动化专业英语原文和翻译

自动化专业毕业设计外文翻译1

自动化专业英语原文和翻译

自动化专业毕业设计(论文)外文翻译-----电子动力转向系统

机械设计制造及其自动化毕业论文中英文资料外文翻译

自动化专业毕业设计外文翻译--输入力矩受限的机器人鲁棒自适应控制

自动化专业毕业设计外文翻译--使用连续小波变换在配电系统中故障定位(中文)

自动化专业英语原文和翻译

自动化专业毕业设计--中英文翻译

自动化专业英语原文和翻译

自动化专业毕业外文翻译