自动化外文翻译
自动化专业毕业论文外文文献翻译
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。
自动化专业外文翻译---模糊逻辑控制机器人走迷宫
外文资料FUZZY LOGIC CONTROL FOR ROBOT MAZE TRA VERSAL: ANUNDERGRADUATE CASE STUDYJames Wolfer Chad A. GeorgeAbstractAs previously reported, Indiana University South Bend has deployed autonomous robots in their Computer Organization course to facilitate introducing computer science students to the basics of logic, embedded systems, and assembly language. The robots help to provide effective, real-time feedback on program operation and to make assembly language less abstract. As a part of their coursework students are required to program a sensor-based traversal of a maze. This paper details one solution to this problem employing a fuzzy logic controller to create linguistic rules.Key words:Fuzzy logic, pedagogy, robots, student projectsINTRODUCTIONAssembly language programming in a computer science environment is often taught using abstract exercises to illustrate concepts and encourage student proficiency.To augment this approach we have elected to provide hands-on, real-world experience to our students by introducing robots into our assembly language class.Observing the physical action of robots can generate valuable feedback and have real-world consequences – robots hitting walls make students instantly aware of program errors, for example.It also provides insight into the realities of physical machines such as motor control, sensor calibration, and noise. To help provide a meaningful experience for our computer organization students, we reviewed the course with the following objectives in mind:• Expand the experience of our students in a manner that enhances the student's insight, provides a hands-on, visual, environment for them to learn, and forms an integrated component for future classes.•Remove some of the abstraction inherent in the assembly language class. Specifically, to help enhance the error detection environment.• Provide a kinesthetic aspect to our pedagogy.• Build student expertise early in their program that could lead to research projects and advanced classroom activities later in their program. Specifically, in this case, to build expertise to support later coursework in intelligent systems and robotics.As one component in meeting these objectives we, in cooperation with the Computer Science department, the Intelligent Systems Laboratory, and the University Center for Excellence in Teaching, designed a robotics laboratory to support the assembly language portion of the computer organization class as described in [1].The balance of this report describes one example project resulting from this environment. Specifically, we describe the results of a student project developing an assembly language fuzzy engine, membership function creation, fuzzy controller, and resulting robot behavior in a Linux-based environment.We also describe subsequent software devlopment in C# under Windows, including graphical membership tuning, real-time display of sensor activation, and fuzzy controller system response. Collectively these tools allow for robust controller development, assemblylanguage support, and an environment suitable for effective classroom and publicdisplay.BACKGROUNDRobots have long been recognized for their potential educational utility, with examples ranging from abstract, simulated, robots, such as Karel[2] and Turtle[3] for teaching programming and geometry respectively, to competitive events such as robotic soccer tournaments[4].As the cost of robotics hardware has decreased their migration into the classroom has accelerated [5, 6]. Driven by the combined goals for this class and the future research objectives, as well as software availability, we chose to use off-the-shelf, Khepera II, robots from K-Team[7].SIMULATED ROBOT DIAGRAMThe K-Team Kephera II is a small, two-motor robot which uses differential wheel speed for steering. Figure 1 shows a functional diagram of the robot. In addition to thetwo motors it includes a series of eight infrared sensors, six along the “front” and two in the “back”of the robot. This robot also comes with an embedded system-call library, a variety of development tools, and the availability of several simulators. The embedded code in the Khepera robots includes a relatively simple, but adequate, command level interface which communicates with the host via a standard serial port. This allows students to write their programs using the host instruction set (Intel Pentium in this case), send commands, and receive responses such as sensor values, motor speed and relative wheel position.We also chose to provide a Linux-based programming environment to our students by adapting and remastering the Knoppix Linux distribution [9]. Our custom distribution supplemented Knoppix with modified simulators for the Khepera, the interface library (including source code),manuals, and assembler documentation. Collectively, this provides a complete development platform.The SIM Kheperasimulator[8] includes source code in C, and provides a workable subset of the native robot command language. It also has the ability to redirect input and output to the physical robot from the graphics display. Figure 2 shows the simulated Khepera robot in a maze environment and Figure 3 shows an actual Khepera in a physical maze. To provide a seamless interface to the simulator and robots we modified the original simulator to more effectively communicate through a pair of Linuxpipes, and we developed a small custom subroutine library callable from the student's assembly language programs.Assignments for the class range from initial C assignments to call the robot routines to assembly language assignments culminating in the robot traversing the maze. FUZZY CONTROLLEROne approach to robot control, fuzzy logic, attempts to encapsulate important aspects of human decision making. By forming a representation tolerant of vague, imprecise, ambiguous, and perhaps missing information fuzzy logic enhances the ability to deal with real-world problems. Furthermore, by empirically modeling a system engineering experience and intuition can be incorporated into a final design.Typical fuzzy controller design [10] consists of:• Defining the control objectives and criteria• Determining the input and output relationships• Creating fuzzy membership functions, along withsubsequent rules, to encapsulate a solution fromintput to output.• Apply necessary input/output conditioning• Test, evaluate, and tune the resulting system.Figure 4 illustrates the conversion from sensor input to a fuzzy-linguistic value. Given three fuzzy possibilities, …too close‟, …too far‟, and …just right‟, along with a sensor reading we can ascertain the degree to which the sensor reading belongs to each of these fuzzy terms. Note that while Figure 4 illustrates a triangular membership set, trapezoids and other shapes are also common.Once the inputs are mapped to their corresponding fuzzy sets the fuzzy attributes are used, expert system style, to trigger rules governing the consequent actions, in this case, of the robot.For example, a series of rules for a robot may include:• If left-sensor is too close and right sensor is too far then turn right.• If left sensor is just right and forward sensor is too far then drive straight.• If left sensor is too far and forward sensor is too far then turn left.• If forward sensor is close then turn right sharply.The logical operators …and‟, …or‟, and …not‟ are calculated as follows: …and‟ represents set intersection and is calculated as the minimum value, …or‟ is calculated as the maximum value or the union of the sets, and …not‟ finds the inverse of the set, calculated as 1.0-fitness.Once inputs have been processed and rules applied, the resulting fuzzy actions must be mapped to real-world control outputs. Figure 5 illustrates this process. Here output is computed as the coordinate of the centroid of the aggregate area of the individual membership sets along the horizontal axis.ASSEMBLY LANGUAGE IMPLEMENTATIONTwo implementations of the fuzzy robot controller were produced. The first was written in assembly language for the Intel cpu architecture under the Linux operating system, the second in C# under Windows to provide a visually intuitive interface for membership set design and public demonstration.Figure 6 shows an excerpt of pseudo-assembly language program. The actual program consists of approximately eight hundred lines of hand-coded assembly language. In the assembly language program subroutine calls are structured with parameters pushed onto the stack. Note that the code for pushing parameters has been edited from this example to conserve space and to illustrate the overall role of the controller. In this code-fragment the …open_pipes‟ routine establishes contact with the simulator or robot. Once communication is established, a continous loop obtains sensor values, encodes them as fuzzy inputs, interprets them through the rule base to linguistic output members which are then converted to control outputs which are sent to the robot. The bulk of the remaining code implements the fuzzy engine itself.FUZZY CONTROLLER MAIN LOOPMembership sets were manually defined to allow the robot to detect and track walls, avoid barriers, and negotiate void spaces in it field of operation. Using this controller, both the simulated robot and the actual Khepera successfully traversed a variety of maze configurations.ASSEMBLY LANGUAGE OBSERV ATIONSWhile implementing the input fuzzification and output defuzzification in assembly language was tedious compared with the same task in a high level language, the logic engine proved to be well suited to description in assembly language.The logic rules were defined in a type of psuedo-code using …and‟, …or‟, …not‟ as operators and using the fuzzy input and output membership sets as parameters. With the addition of input, output and flow control operators, the assembly language logic engine simply had to evaluate these psuedo-code expressions in order to map fuzzy inputs memberships to fuzzy output memberships.Other than storing the current membership fitness values from the inputfuzzyfication, the only data structure needed for the logic engine is a stack to hold intermediate calculations. This is convenient under assembly language since the CPUs stack is immediately available as well as the nescesary stack operators.There were seven commands implemented by the logic rule interpreter: IN, OUT, AND, OR, NOT, DONE, and EXIT.•IN – reads the current fitness from an input membership set and places the value on the stack.•OUT – assigns the value on the top of the stack as the fitness value of an output membership set if it is greater than the existing fitness value for that set.•AND – performs the intersection operation by replacing the top two elements on the stack with the minimum element.•OR – performs the union operation by replace the top two elements on the stack with their maximum.•NOT – replaces the top value on the stack with its compliment.•DONE – pops the top value off the stack to prepare for the next rule•EXIT – signals the end of the logic rule definition and exits the interpreter.As an example the logic rule “If left-sensor is too close and right sensor is too far then turn right”, might be define d by the following fuzzy logic psuedo-code: IN, left_sensor[ TOO_CLOSE ]IN, right_sensor[ TOO_FAR ] ANDOUT, left_wheel[ FWD ]OUT, right_wheel[ STOP ]DONEEXITBy utilizing the existing CPU stack and implementing the logic engine as anpsuedo-code interpreter, the assembly language version is capable of handling arbitrarily complicated fuzzy rules composed of the simple logical operators provided. IMPLEMENTATIONWhile the assembly language programming was the original focus of the project, ultimately we felt that a more polished user interface was desirable for membership set design, fuzzy rule definition, and controller response monitoring. To provide these facilities the fuzzy controller was reimplemented in C# under Windows. through 10 illustrate the capabilities of the resulting software. Specifically, Figure 7 illustrates user interface for membership defination, in this case …near‟. Figure 8 illustrates theinterface for defining the actual fuzzy rules. Figure 9 profiles the output response with respect to a series of simulated inputs. Finally, real-time monitoring of the system is also implemented as illustrated in 10 which shows the robot sensor input values.Since the Khepera simulator was operating system specific, the C# program controls the robot directly. Again, the robot was successful at navigating the maze using a controller specified with this interface.SUMMARYTo summarize, we have developed a student-centric development environment for teaching assembly language programming. As one illustration of its potential we profiled a project implementing a fuzzy-logic engine and controller, along with a subsequent implementation in the C# programming language. Together these projects help to illustrate the viability of a robot-enhanced environment for assembly language programming.REFERENCES[1] Wolfer, J &Rababaah, H. R. A., “Creating a Hands-On Robot Environment for Teaching Assembly Language Programming”, Global Conference on Engineering and Technology Education, 2005[2] Pattic R.E., Karel the Robot: a gentle introduction to the art of programming, 2nd edition. Wiley, 1994[3] Abelson H. and diSessa A., Turtle geometry: the computer as a medium for exploring mathematics. MIT Press, 1996[4] Amirijoo M., Tesanovic A., and Nadjm-Tehrani S., “Raising motivation in real-time laboratories: the soccer scenario” in SIGCSE Technical Symposium on Computer Sciences Education, pp. 265-269, 2004.[5] Epp E.C., “Robot control and embedded systems on inexpensive linux platforms workshop,” in SIGCSE Technical Symposium on Computer Science Education, p. 505, 2004[6] Fagin B. and Merkle L., “Measuring the effectiveness of robots in teaching computer science,” in SIGCSE Technical Symposium on Computer Science Education, PP. 307-311, 2003.[7] K-Team Khepera Robots, , accessed 09/06/05.[8] Michel O., “Khepera Simulator package version 2.0: Freeware mobile robot simulator written at the university of nice Sophia-Antipolis by Olivier Michel. Downloadable from the world wide web. http://diwww.epfl.ch/lami/team/michel/khep-sim, accessed 09/06/05.[9] Knoppix Official Site, , accessed 09/06/05.[10] Earl Cox., The Fuzzy Systems Handbook, Academic Press, New York, 1999.模糊逻辑控制机器人走迷宫James Wolfer Chad A. George摘要美国印第安纳大学南本德已部署在他们的计算机组织课程自主机器人，以方便学生介绍计算机科学逻辑的基础知识，嵌入式系统和汇编语言。
自动化专业常用英语词汇
自动化专业常用英语词汇自动化是一门涉及机械、电子、计算机和控制系统等多个领域的学科，它致力于研究和开辟能够自动执行任务的系统和设备。
在自动化专业的学习和工作中，熟悉和掌握常用的英语词汇是非常重要的。
下面是自动化专业常用英语词汇的详细介绍。
1. Automation - 自动化Automation refers to the use of technology to control and operate a system or process without human intervention. It involves the use of various control systems, such as computers and robots, to perform tasks automatically.2. Control system - 控制系统A control system is a set of devices or software that manages and regulates the behavior of a system. It includes sensors, actuators, controllers, and communication networks that work together to maintain the desired performance of the system.3. Robotics - 机器人技术Robotics is the branch of technology that deals with the design, construction, and operation of robots. It involves the use of mechanical, electrical, and computer engineering principles to create machines that can perform tasks autonomously or with human assistance.4. Sensor - 传感器A sensor is a device that detects and responds to physical inputs, such as light, temperature, pressure, or motion. It converts these inputs into electrical signals that can be processed by a control system.5. Actuator - 执行器An actuator is a device that converts electrical, hydraulic, or pneumatic energy into mechanical motion. It is used to control or move a mechanism or system, such as opening or closing a valve or moving a robotic arm.6. Programmable Logic Controller (PLC) - 可编程逻辑控制器A programmable logic controller (PLC) is a specialized computer used to control and automate industrial processes. It is programmable and can be easily reconfigured to adapt to different tasks or requirements.7. Human-Machine Interface (HMI) - 人机界面The human-machine interface (HMI) is the user interface through which an operator interacts with a control system. It typically consists of a graphical display, buttons, and other input/output devices that allow the operator to monitor and control the system.8. Supervisory Control and Data Acquisition (SCADA) - 监控与数据采集系统Supervisory Control and Data Acquisition (SCADA) is a system used to monitor and control industrial processes. It collects real-time data from various sensors and devices and provides a graphical interface for operators to monitor and control the system.9. Industrial Internet of Things (IIoT) - 工业物联网The Industrial Internet of Things (IIoT) refers to the use of internet-connected devices and sensors in industrial settings to collect and exchange data. It enables real-time monitoring, analysis, and control of industrial processes, leading to improved efficiency and productivity.10. Machine Learning - 机器学习Machine learning is a subset of artificial intelligence that focuses on the development of algorithms and models that allow computers to learn and make predictions or decisions without being explicitly programmed. It is widely used in automation to improve system performance and decision-making.11. Control loop - 控制回路A control loop is a closed-loop system that continuously monitors and adjusts the output of a process to maintain a desired setpoint. It typically consists of a sensor, controller, and actuator that work together to regulate the system.12. Feedback - 反馈Feedback is the process of returning a portion of the output of a system back to the input for comparison and adjustment. It is used in control systems to continuously monitor and correct deviations from the desired performance.13. PID controller - 比例-积分-微分控制器A PID controller is a type of control algorithm that uses proportional, integral, and derivative actions to control a system. It is widely used in automation to achieve accurate and stable control of processes.14. Fault diagnosis - 故障诊断Fault diagnosis is the process of identifying and diagnosing faults or malfunctions in a system. It involves analyzing sensor data, system behavior, and performance to determine the cause of the problem and take appropriate corrective actions.15. Safety system - 安全系统A safety system is a set of measures and devices designed to prevent accidents and ensure the safety of personnel and equipment. It includes emergency stop buttons, safety interlocks, and protective barriers to minimize the risk of injury or damage.以上是自动化专业常用英语词汇的详细介绍。
自动化专业-外文文献-英文文献-外文翻译-plc方面
1、外文原文（复印件)A: Fundamentals of Single-chip MicrocomputerTh e si ng le-ch i p mi cr oc om pu ter is t he c ul mi nat i on o f bo th t h e d ev el op me nt o f th e d ig it al com p ut er an d t he int e gr at ed ci rc ui ta r gu ab ly th e t ow m os t s i gn if ic ant i nv en ti on s o f t h e 20t h c en tu ry[1].Th es e to w t ype s o f a rc hi te ct ur e a re fo un d i n s i ng le—ch ip m i cr oc om pu te r。
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计算机 自动化 外文翻译 外文文献 英文文献 原文
The Application of Visualization Technology in ElectricPower Automation SystemWang Chuanqi, Zou QuanxiElectric Power Automation System Department of Yantai Dongfang Electronics Information IndustryCo., Ltd.Abstract: Isoline chart is widely used chart. The authors have improved the existing isoline formation method, proposed a simple and practical isoline formation method, studied how to fill the isoline chart, brought about a feasible method of filling the isoline chart and discussed the application of isoline chart in electric power automation system.Key words: Visualization; Isoline; Electric power automation systemIn the electric power system industry, the dispatching of electric network becomes increasingly important along with the expansion of electric power system and the increasing demands of people towards electric power. At present, electric network dispatching automation system is relatively advanced and relieves the boring and heavy work for operation staff. However, there is a large amount or even oceans of information. Especially when there is any fault, a large amount of alarm information and fault information will flood in the dispatching center. Faced with massive data, operation staff shall rely on some simple and effective tool to quickly locate the interested part in order to grasp the operation state of the system as soon as possible and to predict, identify and remove fault.Meanwhile, the operation of electric power system needs engineers and analysts in the system to analyze a lot of data. The main challenge that a system with thousands of buses poses for electric power automation system is that it needs to supply a lot of data to users in a proper way and make users master and estimate the state of the system instinctively and quickly. This is the case especially in electric network analyzing software. For example, the displaying way of data is more important in analyzing the relations between the actual trend, planned trend of electric network and the transmission capacity of the system. The application of new computer technology and visualization technology in the electric power automation system can greatly satisfy new development and new demands of electric power automation system.The word “Visualization” originates from English “Visual” and itsoriginal meaning is visual and vivid. In fact, the transformation of any abstract things and processes into graphs and images can be regarded as visualization. But as a subject term, the word “Visualization” officially appeared in a seminar held by National Science Foundation (shortened as NSF) of the USA in February 1987. The official report published after the seminar defined visualization, its covered fields and its recent and long-term research direction, which symbolized that “Visualization” became mature as a subject at the international level.The basic implication of visualization is to apply the principles and methods of computer graphics and general graphics to transforming large amounts of data produced by scientific and engineering computation into graphs and images and displaying them in a visual way. It refers to multi research fields such as computer graphics, image processing, computer vision, computer-aided design (CAD) and graphical user interface (GUI), etc. and has become an important direction for the current research of computer graphics.There are a lot of methods to realize visualization and each method has its unique features and applies to different occasions. Isoline and isosurface is an important method in visualization and can be applied to many occasions. The realization of isoline (isosurface) and its application in the electric power automation system will be explained below in detail.1、 Isoline (Isosurface)Isoline is defined with all such points (x i, y i), in which F(x i, y i)=F i (F i is a set value), and these points connected in certain order form the isoline of F(x,y) whose value is F i…Common isolines such as contour line and isotherm, etc.are based on the measurement of certain height and temperature.Regular isoline drawing usually adopts grid method and the steps are as follows:gridingdiscrete data;converting grid points into numerical value;calculating isoline points; tracing isoline; smoothing and marking isoline; displaying isoline or filling the isoline chart. Recently, some people have brought about the method of introducing triangle grid to solve the problems of quadrilateral grid. What the two methods have in common is to use grid and isoline points on the grid for traveling tracing, which results in the following defects in the drawing process:(1) The two methods use the grid structure, first find out isoline pointson each side of certain quadrilateral grid or triangle grid, and then continue to find out isoline points from all the grids, during which a lot of judgment are involved, increasing the difficulty of program realization. When grid nodes become isoline points, they shall be treated as singular nodes, which not only reduces the graph accuracy but also increases the complexity of drawing.(2) The two methods produce drawn graphs with inadequate accuracy and intersection may appear during traveling tracing. The above methods deal with off-grid points using certain curve-fitting method. That is, the methods make two approximations and produce larger tolerance.(3) The methods are not universal and they can only deal with data of grid structure. If certain data is transformed into the grid structure, interpolation is needed in the process, which will definitely reduce the accuracy of graphs.To solve the problems, we adopt the method of raster graph in drawing isoline when realizing the system function, and it is referred to as non-grid method here. This method needs no grid structures and has the following advantages compared to regular methods:(1) Simple programming and easily realized, with no singular nodes involved and no traveling tracing of isoline. All these advantages greatly reduce the complexity of program design.(2)Higher accuracy. It needs one approximation while regular methods need two or more.(3) More universal and with no limits of grid1.1 Isoline Formation Method of Raster GraphThe drawing of raster graph has the following features: the area of drawing isoline is limited and is composed of non-continuous points. In fact, raster graph is limited by computer screen and what people can see is just a chart formed by thousands of or over ten thousand discrete picture elements. For example, a straight line has limited length on computers and is displayed with lots of discrete points. Due to the limitations of human eyes, it seemscontinuous. Based on the above features, this paper proposes isoline formation method of raster graph. The basic idea of this method is: as computer graphs are composed of discrete points, one just needs to find out all the picture element points on the same isoline, which will definitely form thisisoline.Take the isoline of rectangular mountain area for example to discuss detailed calculation method. Data required in calculation is the coordinates and altitude of each measuring point, i.e., (x i ,y i ,z i ), among which z i represents the altitude of No.i measuring point and there are M measuring points in total. Meanwhile, the height of isoline which is to be drawn is provided. For example, starting from h 0 , an isoline is drawn with every height difference of ∆h0 and total m isolines are drawn. Besides, the size of the screen area to be displayed is known and here (StartX,StartY) represents the top left corner of this area while (EndX ，EndY)represents the low right corner of this area. The calculation method for drawing its isoline is as follows:(1) Find out the value of x i and y i of the top left corner and low right corner points in the drawing area, which are represented by X max ，X min ，Y max ,Y min ;(2)Transform the coordinate (x i ,y i ) into screen coordinate (SX i ,SY i ) and the required transformation formula is as follows:sx i =x i -X min /X max -X min (EndX-StartX)sy i =y i -Y min /Y max -Y min (EndY-StartY)Fig. 1 Height computation sketch(3) i ＝startX,j=StartY; Suppose i ＝startX,j=StartY;(4) Use the method of calculating height (such as distance weighting method and least square method, etc.) to calculate out the height h 1, h 2, h 3 of points (i,j), (i+1,j) and (i,j+1), i.e., the height of the three points P 1, P 2 and P 3 in Fig. 1;(5) Check the value of h 1, h 2, h 3 and determine whether there is any isoline crossing according to the following methods:①k=1,h=h 0；①k=1,h=h 0；②Judge whether (P 1-h)*(P 2-h)≤0 is justified. If justified, continue the next step; otherwise, perform ⑤;③Judge whether ｜P1-h｜=｜P2-h｜ is justified. If justified, it indicates that there is an isoline crossing P1, P2, dot the two points and jumpto (6); otherwise, continue next step;④Judge whether ｜P1-h｜＜｜P2-h｜is justified. If justified, it indicates that there is an isoline crossing P1, dot this point; otherwise, dot P2;⑤Judge whether (P1-h)*(P3-h)≤0 is justified. If justified, continue next step; otherwise, perform ⑧.⑥Judge whether｜P1-h｜＝｜P3-h｜is justified. If justified, dot the twopoints P1\,P3 and jump to (6);otherwise, jump to ⑤;⑦Judge whether｜P1-h｜＜｜P3-h｜is justified. If justified, dot P1; otherwise, dot P3;⑧Suppose k:=k+1 and judge whether k＜m+1 I is justified. If unjustified, continue next step; otherwise, suppose h:=h+∆h0 and return to ②.(6) Suppose j:j+1 and judge whether j<EndY is justified. If unjustified,continue next step; otherwise, return to (4);(7) Suppose i:=i+1 and judge whether i<EndX is justified. If unjustified,continue next step; otherwise, return to (4);(8) The end.In specific program design, in order to avoid repeated calculation, an array can be used to keep all the value of P2 in Column i+1 and another variable is used to keep the value of P3.From the above calculation method, it can be seen th at this method doesn’tinvolve the traveling of isoline, the judgment of grid singular nodes and theconnection of isoline, etc., which greatly simplifies the programming and iseasily realized, producing no intersection lines in the drawn chart.1.2 Griding and Determining NodesTime consumption of a calculation method is of great concern. Whencalculating the height of (i,j), all the contributing points to the height ofthis point need to be found out. If one searches through the whole array, it is very time consuming. Therefore, the following regularized grid method is introduced to accelerate the speed.First, two concepts, i.e., influence domain and influence point set, are provided and defined as follows: Definition 1: influence domain O(P) of node P refers to the largest area in which this nodes has some influence on other nodes. In this paper, it can refer to the closed disc with radius as r (predetermined) or the square with side length as a (predetermined).Definition 2: influence point set S(P)of node P refers to the collection of all the nodes which can influence node P. In this paper, it refers to the point set with the number of elements as n (predetermined), i.e., the number of all the known contributing nodes to the height of node (i,j) can only be n and these nodes are generally n nodes closet to node P.According to the above definition, in order to calculate out the height of any node (i,j), one just needs to find out all the nodes influencing the height of this node and then uses the interpolation method according totwo-dimensional surface fitting. Here, we will explain in detail how to calculate out the height of node (i,j) with Definition 1, i.e., the method of influence domain, and make similar calculation with Definition 2.Grid structure is used to determine other nodes in the influence domainof node (i,j). Irregular area is covered with regular grid, in which the grids have the same size and the side of grid is parallel with X axis and Y axis. The grid is described as follows:(x min,x max,NCX)(y min,y max,NCY)In the formula, x min, y max and x max, y max are respectively the minimum and maximum coordinates of x, y direction of the area; NCX is the number of grids in X direction; NCY is the number of grids in Y direction.Determining which grid a node belongs to is performed in the following two steps. Suppose the coordinate of this node is (x,y). First, respectively calculate its grid No. in x direction and y direction, and the formula is as follows:IX＝NCX*（x-x min)/(xmax-x min)+1；IY＝NCY（y-y min)/(y max-y min)+1。
自动化专业常用英语词汇
自动化专业常用英语词汇自动化专业是现代工程技术领域的重要学科之一，涉及到许多与自动化技术相关的概念和术语。
掌握自动化专业常用的英语词汇对于学习和工作都至关重要。
以下是一些常见的自动化专业英语词汇及其解释，供您参考。
1. Automation - 自动化Automation refers to the use of technology, machinery, and systems to perform tasks or processes with minimal human intervention.2. Control system - 控制系统A control system is a set of devices or software that manages, directs, or regulates the behavior of other devices or systems.3. Sensor - 传感器A sensor is a device that detects and responds to physical or environmental changes, such as temperature, pressure, or motion.4. Actuator - 执行器An actuator is a device that converts electrical, hydraulic, or pneumatic energy into mechanical motion to control or move a system or mechanism.5. Programmable Logic Controller (PLC) - 可编程逻辑控制器A PLC is a digital computer used to control electromechanical processes in industries. It is programmed to automate specific tasks or processes.6. Human Machine Interface (HMI) - 人机界面HMI refers to the interface or interaction between humans and machines. It allows users to monitor and control automated systems through graphical user interfaces.7. Supervisory Control and Data Acquisition (SCADA) - 监控与数据采集系统SCADA is a system that collects and analyzes real-time data from remote devices or processes. It is commonly used in industries to monitor and control large-scale systems.8. Industrial Internet of Things (IIoT) - 工业物联网IIoT refers to the network of interconnected devices, sensors, and systems used in industrial settings to collect and exchange data. It enables automation and data-driven decision-making.9. Robotics - 机器人技术Robotics involves the design, construction, and operation of robots. It combines elements of mechanical engineering, electronics, and computer science to create machines that can perform tasks autonomously or with human guidance.10. Artificial Intelligence (AI) - 人工智能AI refers to the development of computer systems that can perform tasks that normally require human intelligence, such as speech recognition, decision-making, and problem-solving.11. Machine Learning - 机器学习Machine learning is a subset of AI that focuses on the development of algorithms and models that allow computers to learn and improve from data without being explicitly programmed.12. Control loop - 控制回路A control loop is a feedback system used in control systems to continuously monitor and adjust the output based on the desired input or setpoint.13. Feedback - 反馈Feedback is the information or signals received by a control system that allows it to compare the actual output with the desired output and make necessary adjustments.14. Process optimization - 过程优化Process optimization involves improving the efficiency, performance, or quality of a system or process through the use of automation and data analysis.15. Fault diagnosis - 故障诊断Fault diagnosis is the process of identifying and analyzing faults or malfunctions in a system or process. It often involves using sensors, data analysis, and diagnostic algorithms.16. System integration - 系统集成System integration refers to the process of combining different subsystems or components into a unified system that functions as a whole. It involves connecting, configuring, and testing various hardware and software components.17. Industrial control network - 工业控制网络An industrial control network is a communication network used to connect and control devices, sensors, and systems in an industrial environment. It enables data exchange and coordination between different components.18. Safety system - 安全系统A safety system is a set of measures, devices, or procedures designed to prevent accidents, protect personnel, and ensure the safe operation of automated systems.19. Process automation - 过程自动化Process automation refers to the use of technology and systems to automate and streamline industrial processes, reducing human intervention and improving efficiency.20. Data acquisition - 数据采集Data acquisition is the process of collecting and recording data from sensors, devices, or systems. It is an essential step in monitoring and controlling automated processes.以上是一些常见的自动化专业英语词汇及其解释。
自动化用英语怎么说？
自动化用英语怎么说？自动化的英语说法1：robotization自动化的英语说法2：automation自动化相关英语表达：半自动化 semi-automation自动化系 automation department自动化技术 Automation ; automation家庭自动化 Home Automation自动化的英语例句：1. He wanted to use puters to automate the process.他想通过计算机实现流程的自动化。
2. An automatic weather station feeds information on wind direction to the puter.自动化气象站将风向资讯输入计算机。
3. Automation revolutionized the olive industry in the early 1970s.自动化技术在20世纪70年代早期给橄榄油产业带来了一场革命。
4. Automation would bring a shorter, more flexible working week.自动化会使工作周缩短，也更为灵活。
5. Administrative staff may be deskilled through increased automation and efficiency.随着自动化程度和效率的不断提高，对管理人员的技能要求可能会大大降低。
6. The entire manufacturing process has been automated.整个生产过程已自动化。
7. Automation meant the loss of many factory jobs.自动化意味着许多工厂工人失业。
8. Automation will mean the loss of many jobs in this factory.自动化将意味着这个工厂要减少许多工作职位.9. Automation is on the march.自动化在发展中.10. Automation has helped to increase production.自动化促进了生产的发展.11. Automation has obsoleted many unskilled workers.自动化使很多非技术工人受到淘汰.12. In an automated car plant there is not a human operative to be seen.在自动化汽车制造厂看不到一个工人。
自动化专业毕业外文翻译
英文翻译2016届自动化专业 1206111班级姓名学号指导教师职称二О一六年月日THE INTRODUCE OF PLCONE、PLC overviewProgrammable controller is the first in the late 1960s in the United States, then called PLC programmable logic controller (Programmable Logic Controller) is used to replace relays. For the implementation of the logical judgment, timing, sequence number, and other control functions. The concept is presented PLC General Motors Corporation. PLC and the basic design is the computer functional improvements, flexible, generic and other advantages and relay control system simple and easy to operate, such as the advantages of cheap prices combined controller hardware is standard and overall. According to the practical application of target software in order to control the content of the user procedures memory controller, the controller and connecting the accused convenient target.In the mid-1970s, the PLC has been widely used as a central processing unit microprocessor, import export module and the external circuits are used, large-scale integrated circuits even when the PLC is no longer the only logical (IC) judgment functions also have data processing, PID conditioning and data communications functions. International Electro technical Commission (IEC) standards promulgated programmable controller for programmable controller draft made the following definition : programmable controller is a digital electronic computers operating system, specifically for applications in the industrial design environment. It used programmable memory, used to implement logic in their internal storage operations, sequence control, timing, counting and arithmetic operations, such as operating instructions, and through digital and analog input and output, the control of various types of machinery or production processes. Programmable controller and related peripherals, and industrial control systems easily linked to form a whole, to expand its functional design. Programmable controller for the user, is a non-contact equipment, the procedures can be changed to change production processes. The programmable controller has become a powerful tool for factory automation, widely popular replication. Programmable controller is user-oriented industries dedicated control computer, with many distinctive features.First, high reliability, anti-interference capability;Second，programming visual, simple;Third, adaptability good;Fourth functional improvements, strong functional interface.TWO、History of PLCProgrammable 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 or so-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 PLCs 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 PLCs are 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 PLCs are dropping continuously, reducing the scan time of the ladder logic is still an issue in industry so that low-cost PLCs 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 of the manpower allocated for the control system design and installation is scheduled for testing and debugging PLC programs.In addition, current PLC based control systems are not properly designed to support the growing demand for flexibility and reconfigurability of manufacturing systems. A further problem, impelling the need for a systematic design methodology, is the increasingsoftware 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.Three、now of PLCFrom the structure is divided into fixed PLC and Module PLC, the two kinds of PLC including CPU board, I/O board, display panel, memory block, power, these elements into a do not remove overall. Module type PLC including CPU module, I/O modules, memory, the power modules, bottom or a frame, these modules can be according to certain rules combination configuration.In the user view, a detailed analysis of the CPU's internal unnecessary, but working mechanism of every part of the circuit. The CPU control works, by it reads CPU instruction, interprets the instruction and executes instructions. But the pace of work by shock signal control.Unit work under the controller command used in a digital or logic operation.In computing and storage register of computation result, it is also among the controller command and work. CPU speed and memory capacity is the important parameters for PLC , its determines the PLC speed of work, IO PLC number and software capacity, so limits to control size.Central Processing Unit (CPU) is the brain of a PLC controller. CPU itself is usually one of the microcontrollers. Aforetime these were 8-bit microcontrollers such as 8051, and now these are 16-and 32-bit microcontrollers. Unspoken rule is that you’ll find mostly Hitachi and Fujicu microcontrollers in PLC controllers by Japanese makers, Siemens in European controllers, and Motorola microcontrollers in American ones. CPU also takes care of communication, interconnectedness among other parts of PLC controllers, program execution, memory operation, overseeing input and setting up of an output.System memory (today mostly implemented in FLASH technology) is used by a PLC for a process control system. Aside form. this operating system it also contains a user program translated forma ladder diagram to a binary form. FLASH memory contents can be changed only in case where user program is being changed. PLC controllers were used earlier instead of PLASH memory and have had EPROM memory instead of FLASH memory which had to be erased with UV lamp and programmed on programmers. With the use of FLASH technology this process was greatly shortened. Reprogramming a program memory is done through a serial cable in a program for application development.User memory is divided into blocks having special functions. Some parts of a memory are used for storing input and output status. The real status of an input is stored either as “1”or as “0”in a specific memory bit/ each input or output has one corresponding bit in memory. Other parts of memory are used to store variable contents for variables used in used program. For example, time value, or counter value would be stored in this part of the memory.PLC controller can be reprogrammed through a computer (usual way), but also through manual programmers (consoles). This practically means that each PLC controller can programmed through a computer if you have the software needed for programming. Today’s transmission computers are ideal for reprogramming a PLC controller in factory itself. This is of great importance to industry. Once the system is corrected, it is also important to read the right program into a PLC again. It is also good to check from time to time whether program in a PLC has not changed. This helps to avoid hazardous situations in factory rooms (some automakers have established communication networks which regularly check programs in PLC controllers to ensure execution only of good programs).Almost every program for programming a PLC controller possesses various useful options such as: forced switching on and off of the system input/outputs (I/O lines), program follow up in real time as well as documenting a diagram. This documenting is necessary to understand and define failures and malfunctions. Programmer can add remarks, names of input or output devices, and comments that can be useful when finding errors, or with system maintenance. Adding comments and remarks enables any technician (and not just a person who developed the system) to understand a ladder diagram right away. Comments and remarks can even quote precisely part numbers if replacements would be needed. This would speed up a repair of any problems that come up due to bad parts. The old way was such that a person who developed a system had protection on the program, so nobody aside from this person could understand how it was done. Correctly documented ladder diagram allows any technician to understand thoroughly how systemfunctions.Electrical supply is used in bringing electrical energy to central processing unit. Most PLC controllers work either at 24 VDC or 220 VAC. On some PLC controllers you’ll find electrical supply as a separate module. Those are usually bigger PLC controllers, while small and medium series already contain the supply module. User has to determine how much current to take from I/O module to ensure that electrical supply provides appropriate amount of current. Different types of modules use different amounts of electrical current.This electrical supply is usually not used to start external input or output. User has to provide separate supplies in starting PLC controller inputs because then you can ensure so called “pure” supply fo r the PLC controller. With pure supply we mean supply where industrial environment can not affect it damagingly. Some of the smaller PLC controllers supply their inputs with voltage from a small supply source already incorporated into a PLC.Four、PLC design criteriaA 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, theprogramming of PLCs 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 [IEC 60848, 1999; IEC-61131-3, 1993; IEC 61499, 1998; ISO 15745-1, 1999] 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.Today, the primary focus of most design research is based on mechanical or electrical products. One of the by-products of this proposed research is to enhance our fundamental understanding of design theory and methodology by extending it to the field of engineering systems design. A system design theory for large-scale and complex system is not yet fully developed. Particularly, the question of how to simplify a complicated or complex design task has not been tackled in a scientific way. Furthermore, building a bridge between design theory and the latest epistemological outcomes of formal representations in computer sciences and operations research, such as discrete event system modeling, can advance future development in engineering design.From a logical perspective, PLC software design is similar to the hardware design ofintegrated circuits. Modern VLSI designs are extremely complex with several million parts and a product development time of 3 years [Whitney, 1996]. The design process is normally separated into a component design and a system design stage. At component design stage, single functions are designed and verified. At system design stage, components are aggregated and the whole system behavior and functionality is tested through simulation. In general, a complete verification is impossible. Hence, a systematic approach as exemplified for the PLC program design may impact the logical hardware design.Five、AK 1703 ACPFollowing the principle of our product development, AK 1703 ACP has high functionality and flexibility, through the implementation of innovative and reliable technologies, on the stable basis of a reliable product platform.For this, the system concept ACP (Automation, Control and Protection) creates the technological preconditions. Balanced functionality permits the flexible combination of automation, telecontrol and communication tasks. Complemented with the scalable performance and various redundancy configurations, an optimal adaptation to the respective requirements of the process is achieved.AK 1703 ACP is thus perfectly suitable for automation with integrated telecontrol technology as:• Telecontrol substation or central device• Auto mation unit with autonomous functional groups• Data node, station control device, front-end or gateway• With local or remote peripherals• For rear panel installation or 19 inch assembly• Branch-neutral product, therefore versatile fields of application and high productstability• Versatile communication• Easy engineering• Plug & play for spare parts• Open system architecture• Scalable redundancy• The intelligent terminal - TM 1703The Base Unit AK 1703 ACP with Peripheral Elements has one basic system element CP-2010/CPC25 (Master control element) and CP-2012/PCCE25 (Processing andcommunication element) ,one bus line with max. 16 peripheral elements can be connected.CP-2010/CPC25 Features and FunctionsSystem Functions:• Central element,coordina ting all system servicesCentral hub function for all connected basic system elements• Time managementCentral clock of the automation unitSetting and keeping the own clock`s time with a resolution of 10msSynchronization via serid communication via LAN or local• RedundancyVoting and change-over for redundant processing and communication elements of the own automation unitSupports voting and change-over by an external SCA-RS redundancy switchSupports applicational voting and change-over by an external system,e.g.a control system• SAT TOLLBOX|| connectionStoring firmware and parameters on a Flash CardCommunication:• Communication via installable protocol elements to any superior or subordinate automation unit• Automatic data flow routing• Priority based data transmission (priority control)• Own circular buffer and process image for each connected station(data keeping)• Redundant communication routesCommunication with redundant remote stations• Special application specific functions for dial-up trafficTest if stations are reachableProcess Peripherals:• Transmission of spontaneous information objects from and to peripheral elements, via the serial Ax 1703 peripheral busFunctions for Automation:• Open-/closed-loop control function for the execution of freely definable user programs which are created with CAEX plus according to IEC 61131-3,ing function diagram technology512KB for user programApprox 50.000 variables and signals,2.000 of them retainedCycle of 10ms or a multiple thereofOnline testLoadable without service interruption• Redundant open-/closed-loop control functionsSynchronization via redundancy linkTransmission of periodic process information between the open-/closed-loop control function and the peripheral elements,via the serial Ax 1703 peripheral bus.Six、SIEMENS PLCSIMATIC S7-300 series PLC applied to all walks of life and various occasions in the detection, monitoring and control of automation, its power to both the independent operation of, or connected to a network able to achieve complex control.The photoelectric products with isolation, high electromagnetic compatibility; have high industrial applicability, allowing the ambient temperature of 60 ℃; has strong anti-jamming and anti-vibration and impact resistance, so in a harsh working environment has been widely Applications.I also mean freedom of communication S7-300 type PLC' s a very unique feature, which allows S7-300-PLC can deal openly with any other communications equipment, communications controller, or PLC S7-300 type can be defined by the user's own Communications protocol (of the agreement ASCII), the baud rate to 1.5 Mbit / s (adjustable). So that can greatly increase the scope of communications so that the control system configuration more flexible and convenient. Of any kind with a serial interface peripherals, such as: printers or bar code readers, Drives, a modem (Modem), the top PC-connected, and so can be used. Users can program to develop communication protocols, the exchange of data (for example: ASCII character code), RS232 interfaces with the equipment can also be used PC / PPI cable linking the free communication communications.When the PC offline, under the control of the next crew, the whole system can operate normally.PC that is by control centre, mainly by the PC and laser printer components, using SIMATIC WINCC software platform, the all-Chinese interface, friendly man-machine dialogue. Managers and operators can be observed through a PC, shown in the various kinds of information to understand the present and pion tasks.WINCC and the ice-storage operation of the automatic control system and all theparameters, and through the mouse to print equipment management and implement at software in the field of automation can be used for all the operators’ control and monitoring tasks. Can be controlled in the process of the events clearly show, and shows the current status and order records, the recorded data can show all or select summary form, or may be required for editing, printing and output statements and trends .WINCC able to control the critical situation in the early stages of the report, and the signal can be displayed on the screen, can also use sound to be felt. It supported by online help and operational guidelines to eliminate failure. WINCC a workstation can be devoted to the process control to the process so that important information not is shielded. Software-assisted operation strategy ensures that the process was not illegal to visit and to provide for non-industrial environment in the wrong operation.WINCC is MICRSOFT WINDOWS98 or WINDOWS NT4.0 operating system, running on a PC object-oriented class 32-bit applications, OLE through the window and ODBC standard mechanism, as an ideal partner to enter the communications world WINDOWS, it can be easily WINCC To integrate a company-wide data processing system.可编程控制器的介绍一、PLC概述可编程控制器是60年代末在美国首先出现的，当时叫可编程逻辑控制器PLC（Programmable Logic Controller），目的是用来取代继电器。
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。
自动化专业翻译必备词汇
自动化专业翻译必备词汇自动化专业是现代工程技术中的重要领域，涉及到各种自动化系统的设计、开发和应用。
在进行自动化专业翻译时，熟悉相关的专业术语是非常重要的。
下面是一些自动化专业翻译中必备的词汇及其解释，以帮助您更好地理解和翻译相关文本。
1. Automation（自动化）Automation refers to the use of technology to perform tasks with minimal human intervention. It involves the design and implementation of systems or processes that can operate automatically.2. Control system（控制系统）A control system is a set of devices or software that manages, regulates, and directs the behavior of other devices or systems. It ensures that the desired output is achieved by adjusting the input or parameters.3. PLC（可编程逻辑控制器）PLC stands for Programmable Logic Controller. It is a digital computer used for automation of electromechanical processes. PLCs are widely used in industrial control systems to monitor and control machinery and processes.4. SCADA（监控与数据采集系统）SCADA stands for Supervisory Control and Data Acquisition. It refers to a system that collects and analyzes real-time data from various remote locations. SCADA systems are commonly used in industries such as power plants, water treatment plants, and manufacturing facilities.5. HMI（人机界面）HMI stands for Human-Machine Interface. It is a graphical interface that allows users to interact with machines or systems. HMIs provide visual representations of data and enable operators to control and monitor processes.6. Sensor（传感器）A sensor is a device that detects and responds to physical or environmental changes. It converts the measured data into electrical signals that can be processed by other devices or systems. Sensors are used to collect data for automation and control purposes.7. Actuator（执行器）An actuator is a device that converts electrical signals into physical action. It is used to control or move mechanical systems. Actuators are commonly used in automation systems to perform specific tasks or functions.8. Robotics（机器人技术）Robotics refers to the design, construction, and operation of robots. Robots are programmable machines that can perform tasks autonomously or with minimal human intervention. Robotics is an important field in automation technology.9. Industrial Internet of Things (IIoT)（工业物联网）IIoT refers to the network of interconnected devices, sensors, and systems in an industrial setting. It enables the exchange of data and information between machines, allowing for improved automation, efficiency, and productivity.10. Control algorithm（控制算法）A control algorithm is a set of mathematical equations or rules that determine how a control system behaves. It defines the relationship between the input and output variables and guides the system's response to achieve the desired control objectives.11. Feedback loop（反馈环路）A feedback loop is a mechanism in a control system that uses the output of a process to modify the input or parameters. It allows the system to continuously adjust and improve its performance based on the feedback received.12. PID controller（比例积分微分控制器）PID controller stands for Proportional-Integral-Derivative controller. It is a control algorithm widely used in industrial automation. The PID controller continuously calculates and adjusts the control signal based on the error between the desired setpoint and the measured process variable.13. Programmable automation（可编程自动化）Programmable automation refers to the use of programmable devices or systems to automate processes or tasks. It allows for flexibility and adaptability in changing or reprogramming the automation logic as needed.14. System integration（系统集成）System integration is the process of combining different subsystems or components into a unified and cohesive system. It involves connecting and coordinating various hardware and software elements to ensure seamless operation and communication.15. Fault diagnosis（故障诊断）Fault diagnosis is the process of identifying and analyzing faults or malfunctions in a system. It involves detecting, isolating, and troubleshooting problems to restore the system's normal operation.以上是一些自动化专业翻译中常用的词汇及其解释。
自动化专业常用英语词汇
自动化专业常用英语词汇1. Automation (自动化): The use of technology to control and operate processes or systems with minimal human intervention.2. Control system (控制系统): A system that manages and regulates the behavior of other systems or processes.3. Programmable logic controller (PLC) (可编程逻辑控制器): A digital computer used for automation of electromechanical processes, such as control of machinery on factory assembly lines.4. Human-machine interface (HMI) (人机界面): The interface that allows humans to interact with and control machines or systems.5. Sensor (传感器): A device that detects and responds to physical inputs, such as temperature, pressure, or light, and converts them into electrical signals.6. Actuator (执行器): A device that converts electrical or mechanical signals into physical motion or action, such as a motor or a solenoid.7. Feedback control (反馈控制): A control system that uses information from sensors to continuously adjust and maintain a desired output or behavior.8. Process optimization (过程优化): The act of improving a system or process to achieve maximum efficiency, productivity, or quality.9. Robotics (机器人技术): The branch of technology that deals with the design, construction, operation, and use of robots.10. Industrial Internet of Things (IIoT) (工业物联网): The application of Internet of Things (IoT) technology in industrial settings, enabling the interconnection and communication of devices, sensors, and systems.11. Data acquisition (数据采集): The process of gathering and collecting data from various sources, such as sensors or instruments, for further analysis and processing.12. Supervisory control and data acquisition (SCADA) (监控与数据采集系统): A system that allows for remote monitoring and control of industrial processes or infrastructure, typically through a centralized computer system.13. Programmable automation controller (PAC) (可编程自动化控制器): A type of industrial control system that combines the features of a PLC and a PC, providing greater flexibility and processing power.14. Distributed control system (DCS) (分布式控制系统): A control system that consists of multiple autonomous controllers distributed throughout a plant or facility, allowing for decentralized control and monitoring.15. Industrial robot (工业机器人): A robot designed specifically for industrial applications, such as assembly, welding, or material handling.16. Fault diagnosis (故障诊断): The process of identifying and analyzing faults or malfunctions in a system or process, often using diagnostic tools or techniques.17. Motion control (运动控制): The technology and techniques used to control the movement and positioning of machines or systems, typically through the use of motors and servo drives.18. Safety system (安全系统): A system designed to protect personnel, equipment, and the environment from potential hazards or accidents in an industrial or automation setting.19. Process control (过程控制): The use of control systems and techniques to regulate and maintain the desired behavior or output of a process, such as temperature, pressure, or flow rate.20. Simulation (摹拟): The imitation or representation of the operation or behavior of a real-world system or process using a computer model, often used for testing and optimization purposes.以上是自动化专业常用英语词汇的详细介绍，希翼对您有所匡助。
自动化专业中英文对照外文翻译文献
中英文对照外文翻译Automation of professional developmentAutomation in the history of professional development, "industrial automation" professional and "control" professional development of the two main line, "industrial automation" professional from the first "industrial enterprises electrified" professional.In the 1950s, the New China was just founded, the 100-waste question, study the Soviet Union established system of higher education, Subdivision professional. Corresponding to the country in the construction of industrial automation and defense, military construction in automatic control, successively set up the "electrification of industrial enterprises" professional and "control" professional (at that time in many schools, "Control" professional secrecy is professional) . After several former professional name of evolution (see below), and gradually develop into a "biased towards applications, biased towards strong," Automation, and the latter to maintain professional name of "control" basically unchanged (in the early days also known as the "automatic learning And remote learning, "" Automatic Control System "professional), and gradually develop into a" biased towards theory, biased towards weak, "the automation professional, and come together in 1995, merged into aunified" automatic "professional . In 1998, according to the Ministry of Education announced the latest professional undergraduate colleges and universities directory, adjusted, the merger of the new "automated" professional include not only the original "automatic" professional (including "industrial automation" professional and "control" professional ), Also increased the "hydraulic transmission and control of" professional (part), "electrical technology" professional (part) and "aircraft guidance and control of" professional (part).Clearly, one of China's automation professional history of the development of China's higher education actually is a new development of the cause of a microcosm of the history, but also the history of New China industrial development of a miniature. Below "industrial automation" professional development of the main line of this example, a detailed review of its development process in the many professional name change (in real terms in the professional content changes) and its industrial building at the time of the close relationship.First a brief look at the world and China's professional division history. We know that now use the professional division is largely from the 19th century to the beginning of the second half of the first half of the 20th century stereotypes of the engineering, is basically industry (products) for the objects to the division, they have been the image of people Known as the "industry professionals" or "trade associations." At present the international education system in two categories, with Britain and the United States as the representative of the education system not yet out of "industry professionals" system, but has taken the "generalist" the road of education and the former Soviet Union for Europe (close to the Soviet Union) as the representative The education system, at the beginning of theimplementation of "professionals" education, professional-very small, although reforms repeatedly, but to the current "industry professionals" are still very obvious characteristics.In the 1950s, just after the founding of New China, a comprehensive study and the Soviet Union and sub-professional very small; Since reform and opening up, only to Britain and the United States to gradually as the representative of the education system to move closer, and gradually reduce the professional, the implementation of "generalist" education through a number of professional Restructuring and merger (the total number of professionals from the maximum of 1,343 kinds of gradually reducing the current 249 kinds), although not out of "industry professionals" and "Mei Ming," but many of the colleges and universities, mostly only one of a Professional, rather than the past more than a professional.Before that, China's first professional automation from the National University in 1952 when the first major readjustment of the establishment of professional - electrified professional industrial enterprises. At that time, the Soviet Union assistance to the construction of China's 156 large industrial enterprises, automation of much-needed electrical engineering and technical personnel, and such professional and technical personnel training, and then was very consistent with China's industrial construction. By the 1960s, professional name changed to "industrial electric and automation," the late 1970s when to resume enrollment "Electric Industrial Automation" professional. This is not only professional name changes, but has its profound meaning, it reflects China's industries from "electrified" step by step to the "automatic" into the real history and that part of the development trend of China's automation professional reflects how urgent countries Urgent for the country'seconomic construction services that period of history and development of real direction.1993, after four years of the third revision of the undergraduate professional directories, the State Education Commission issued a call "system integrity, more scientific and reasonable, the harmonization of norms," the "ordinary professional directory of undergraduate colleges and universities." "Electric Industrial Automation" and "production process automation" merger of the two professional electrician to set up a kind of "industrial automation" professional, by the then Ministry of Industry Machinery centralized management colleges and universities to set up industrial automation teaching guide at the Commission, responsible for the "Industrial Automation "professional teaching and guiding work at the same time," Control "was attributable to the professional category of electronic information, the then Ministry of Industry of electronic centralized management control to set up colleges and universities teaching guide at the Commission, responsible for the" control " Professional teaching guide our work. After the professional adjustment, further defined the "industrial automation" professional and "control" professional "- both strong and weak, hardware and software into consideration and control theory and practical system integration, and the movement control, process control and other targets of control "The common characteristics with the training objectives, but also the basic set of" industrial automation "biased towards strong, professional, biased towards applications," Control "professional biased towards weak, biased towards the theory of professional characteristics and pattern of division of labor. 1995, the State Education Commission promulgated the "(University) undergraduate engineering leading professional directory", the electrical category "industrialautomation" professional and the original electronic information such as "control" of professional electronic information into a new category of "automatic" professional . As this is the leading professional directory, are not enforced, coupled with general "industrial automation" strong or weak, both professional "into" a weak professional category of electronic information is not conducive to professional development and thus many Schools remain "industrial automation" professional and "control" the situation of professional co-exist. Since 1996 more, again commissioned by the Ministry of National Education Ministry of Industry and electronic machinery industries of other parts of the establishment of the new session (second session) centralized management guidance at the University Teaching Commission, making the leading professionals have not been effective Implemented.1998, to meet the country's economic construction of Kuan Koujing personnel training needs, further consolidation of professional and international "generalist" education track by the Ministry of Education announced a fourth revision of the latest "Universities Undergraduate Catalog." So far in the use of the directory, the total number of professionals from the third amendments to the 504 kinds of substantially reduced to 249 species, the original directory is strong, professional electrician and a weak professional category such as electronics and information into categories Electric power, the unity of Information, a former electrician at the same time kind of "industrial automation" professional and the type of electronic information "control" professional formal merger, together with the "hydraulic transmission and control of" professional (part) , "Electric technology" professional (part) and "aircraft guidance and controlof" professional (part), the composition of the new (enforcement) are electrical information such as "automatic" professional. According to statistics, so far the country has more than 200 colleges and universities set up this kind of "automatic" professional. If the name of automation as part of their professional expertise (such as "electrical engineering and automation," "mechanical design and manufacturing automation," "agricultural mechanization and automation" and other professionals) included Automation has undoubtedly is the largest in China A professional.Of the characteristics of China's automation professional:Recalling China's professional history of the development of automation, combined with the corresponding period of the construction of China's national economy to the demand for automation and automated the development of the cause, it is not difficult to sum up following professional characteristics:(1) China's automation professional is not only a relatively long history (since 1952 have been more than 50 years), and from the first day of the establishment of professional automation, has been a professional one of the countries in urgent need, therefore the number of students has also been The largest and most employers welcome the allocation of the professional one.(2) China's automation is accompanied by a professional from the electrification of China's industrial automation step by step to the development of stable development, professional direction and the main content from the first prominent electrified "the electrification of industrial enterprises" step by step for the development of both the electric and automation " Industrial electric and automation ", highlighting the electrical automation" Electric Industrial Automation "and prominent automation" industrial automation ", then the merger of professional education reform in1995 and" control "of professional content into a broader" automated " Professional. From which we can see that China's automation professional Although the initial study in the Soviet education system established under the general environment, but in their development and the Soviet Union or the United States and Britain did not copy the mode, but with China's national conditions (to meet national needs for The main goal) from the innovation and development of "cross-industry professionals," features the professional.自动化专业的发展自动化专业的发展历史中，有“工业自动化”专业与“自动控制”专业两条发展主线，其中“工业自动化”专业最早源于“工业企业电气化”专业。
easy_trans 使用实例
easy_trans 使用实例关于使用easy_trans的实例，我将从简单到复杂，一步一步地回答你的问题，以帮助你更好地理解这个工具。
首先，让我们了解什么是easy_trans。
easy_trans是一个自动化翻译工具，它使用机器学习技术将文本从一种语言转换为另一种语言。
它可以帮助你在不同语言之间快速翻译文本，省去了手动翻译的繁琐过程。
使用easy_trans非常简单。
下面我将以几个实例来演示它的用法。
实例一：单词翻译假设你正在学习英语，并且想要知道"apple"这个单词的中文意思。
你可以通过以下步骤使用easy_trans进行翻译：1. 打开easy_trans应用程序或访问官方网站。
2. 在文本框中输入要翻译的单词"apple"。
3. 在语言选择框中，选择从英文到中文。
4. 单击"翻译"按钮，等待片刻，easy_trans将自动将"apple"翻译为"苹果"。
实例二：句子翻译假设你接触到了一篇德语文章，但你对德语并不熟悉。
你想要了解这篇文章的大致内容，那么你可以使用easy_trans进行句子级的翻译：1. 将德语句子复制到easy_trans的文本框中。
2. 在语言选择框中，选择从德语到中文。
3. 单击"翻译"按钮，easy_trans会自动将整个句子翻译成中文。
实例三：文本翻译假设你是一名编辑，需要将一篇500字的法语文章翻译成英文。
你可以使用easy_trans来进行批量翻译：1. 将法语文章复制到easy_trans的文本框中。
2. 在语言选择框中，选择从法语到英语。
3. 单击"翻译"按钮，easy_trans将整篇文章翻译成英文。
4. 将翻译完成的英文文本复制粘贴到你的编辑软件中进行进一步的编辑和修正。
实例四：网页翻译假设你在浏览一个对你来说陌生的外语网页。
自动化专业常用英语词汇
自动化专业常用英语词汇自动化专业是一门涉及自动控制、机器人技术、工业自动化以及相关领域的学科。
在学习和实践中，掌握一些常用的英语词汇对于自动化专业学生来说非常重要。
以下是一些常见的自动化专业常用英语词汇及其解释。
1. Automation（自动化）Automation refers to the use of technology to control and operate machines or processes without human intervention. It involves the use of various control systems, sensors, and actuators to achieve automatic operation.2. Control system（控制系统）A control system is a set of devices or software that manages and regulates the behavior of other devices or systems. It is used to monitor and control the operation of machines, processes, or equipment.3. Robotics（机器人技术）Robotics is the branch of technology that deals with the design, construction, operation, and application of robots. It involves the study of mechanical engineering, electrical engineering, and computer science to create intelligent machines capable of performing tasks autonomously or with human interaction.4. Industrial automation（工业自动化）Industrial automation refers to the use of various control systems, computer systems, and information technologies to automate industrial processes and manufacturing operations. It aims to increase efficiency, productivity, and safety in industrial settings.5. Programmable logic controller (PLC)（可编程逻辑控制器）A programmable logic controller (PLC) is a digital computer used to control and automate electromechanical processes in industrial settings. It is programmed usingladder logic or other programming languages to monitor and control the operation of machines and processes.6. Human-machine interface (HMI)（人机界面）A human-machine interface (HMI) is a device or software that allows humans to interact with machines or systems. It provides a graphical user interface (GUI) or a touch screen interface for users to monitor and control the operation of machines or processes.7. Sensor（传感器）A sensor is a device that detects and responds to physical or chemical changes in the environment. In automation, sensors are used to measure various parameters such as temperature, pressure, flow, and position, and provide feedback to the control system for decision-making.8. Actuator（执行器）An actuator is a device that converts electrical, hydraulic, or pneumatic energy into mechanical motion. It is used to control and move mechanical components or systems in response to signals from the control system.9. Process control（过程控制）Process control involves monitoring and controlling the variables in a manufacturing or industrial process to ensure optimal performance and product quality. It uses various control strategies and techniques to regulate variables such as temperature, pressure, flow, and level.10. Industrial network（工业网络）An industrial network is a communication system used to connect and exchange data between devices, machines, and systems in an industrial environment. It enables real-time monitoring, control, and coordination of industrial processes and equipment.11. Supervisory control and data acquisition (SCADA)（监控与数据采集）Supervisory control and data acquisition (SCADA) is a system used to monitor and control industrial processes and infrastructure. It collects data from sensors and devices, displays real-time information, and allows operators to control and manage the operation of the system.12. Distributed control system (DCS)（分布式控制系统）A distributed control system (DCS) is a control system that consists of multiple control elements distributed throughout a plant or industrial facility. It allows for decentralized control and coordination of various processes and equipment.以上是一些常见的自动化专业常用英语词汇及其解释。
自动化专业文献英语词汇
自动化专业文献英语词汇
本文是一份关于自动化专业文献英语词汇的汇总，旨在帮助读者更好地理解和使用自动化领域的相关文献。
以下是一些常见的自动化专业词汇及其英语表达：
1. 自动化 (Automation)
2. 控制系统(Control System)
3. 传感器(Sensor)
4. 机器人(Robot)
5. 人机交互(Human-Machine Interaction)
6. 编程(Programmability)
7. 数据采集(Data Acquisition)
8. 系统集成(System Integration)
9. 电气工程(Electrical Engineering)
10. 机械工程(Mechanical Engineering)
11. 控制算法(Control Algorithm)
12. 可编程逻辑控制器(Programmable Logic Controller)
13. 工业网络(Industrial Network)
14. 自适应控制(Adaptive Control)
15. 人工智能(Artificial Intelligence)
16. 机器学习(Machine Learning)
17. 监控系统(Monitoring System)
18. 过程控制(Process Control)
19. 无人驾驶(Unmanned Driving)
20. 自动驾驶(Autonomous Driving)
以上仅是自动化领域的一部分英语词汇，希望读者在学习和研究自动化专业文献时能有所帮助。
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。
自动化英语翻译
自动化英语翻译Automatic English TranslationWith the advancement of technology, automatic English translation has become increasingly popular and widely used. It refers to the process of using computer programs or algorithms to translate text from one language to another.Automatic English translation offers several advantages. First and foremost, it saves a significant amount of time and effort. Instead of manually translating each word or sentence, a computer program can quickly translate the entire text in a matter of seconds. This is especially beneficial when dealing with large volumes of text or when time is limited.In addition, automatic English translation ensures consistency in translation. By using predefined algorithms and rules, the translation remains consistent throughout the text. This is particularly important when translating technical documents or legal texts, where accuracy and consistency are crucial.Furthermore, automatic English translation can be cost-effective. Hiring professional translators can be expensive, especially for small businesses or individuals. With automatic translation tools, the cost is significantly reduced, making it more accessible to a wider range of users.However, automatic English translation has its limitations. One major challenge is the accuracy of the translations. While automatic translation tools have improved over the years, they arestill prone to errors and may not always capture the nuances and context of the original text. This can lead to misunderstandings or misinterpretations, especially in sensitive or complex texts.Another limitation is the lack of cultural understanding. Language is deeply rooted in culture, and automatic translation tools may not always consider cultural differences or nuances. This can result in translations that are technically correct but culturally inappropriate or insensitive.Moreover, automatic English translation may not be suitable for certain types of texts. Creative writing, poetry, and literary works, for example, require a level of creativity and linguistic expertise that automatic translation tools may not possess. In these cases, human translators are still preferred to accurately convey the original meaning and style.In conclusion, automatic English translation has become a valuable tool in today's fast-paced world. It offers time-saving, cost-effective, and consistent translations. However, it is important to be aware of its limitations and to use it judiciously. For accurate and culturally sensitive translations, human translators are still essential.。
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电气工程与自动化学院本科毕业设计专业翻译资料（中文读书报告）学生姓名：***专业班级：自动化12-06班学号：************2016 年 6 月11 日原文：Design of Combustible Gas Detection system using WirelessTransmission TechnologyShijiazhuang Universities of Economics, Hebei, China**************Keywords:TGS813, AT89S52, DS18B20, nRF905, TC35iAbstract.The detection device of combustible gas are designed in the presented work,using wireless transceiver and GSM network.The system realize the wireless transmission of the gas concentration,and also can send alarm information to user’s mobile when an exception occurs.The system consists of two parts: a master and slave. The function of the slave is to collect data, process data and transffer the data to the master.The taskof the master is to receive data and display it by LED.The signal acquisition is completed by sensor TGS813 and A/D converter TLC2543. The wireless transmission is achieved through wireless transceiver nRF905. Since the accuracy of the sensor is affected by the environment,using DS18B20 to achieve temperature compensation.And with wireless communication module TC35i and GSM network platform, we can send the alarm information to user’s mobile promptly.IntroductionGas detection is widely used in petroleum, chemical, metallurgy, family, shopping malls,gas stations and other places. Currently, how to monitor the hazardous gas fast and accuratelyare the important issues. Although the gas detection technology is relatively mature, but most products has many shortcomings, such as single function, operating complex, bulky, expensiveand low sensitivity. Wireless communication technology applied to the gas monitoring field, can resolve the problem of remote monitoring in special environment, such as high temperature, low temperature, toxic gas.and unable to wiring .In the presented work, the combustible gas detectoris fully functional (with wireless transceiver), simple, small size, low cost, and has high sensitivity. The equipment can greatly improve the system's detection capability and accuracy with temperature compensation algorithm, and also can send alarm information to the user's mobile phone promptly through theGSM network.System designThe system consists of two parts as shown in Figure 1.Fig. 1 Overall system block diagramThe slave part mainly complete data collection and wireless transmission. The master part mainly complete receiving data, displaying and sending alarm message.The signal of gas concentration is collected by combustible gas sensor which generates a weak electrical signal. The signal can be amplified and stabilized by conditioning circuit. And then A/D circuit converts the analog signal to digital signal which microcontroller can process. In order to improve the measurement accuracy, and reduce the impact of temperature, design a temperature compensation circuit to collect tempreture data. AT89S52 process the collected data and send data to the master by wireless transceiver.The master receives the data and displays it by LED. And if the gas concentration being abnormal,the system will drive speaker for an alarm signal and use TC35i module to send alarm information to user’s mobile.Hardware designSignal acquisition and conditioning circuit. Figure 2 shows data acquisition circuit. TGS813 is a Gas sensing resistive sensor. The conductivity of TGS813 is influenced by the concentration of combustible gases in air, the greater the concentration, the higher conductivity. In system R0, R9, R10 and RS (inTGS813) form a bridge circuit to convert resistance to voltage signal. Operational amplifier A connected as a voltage follower with resistors R7 and regulator D1 make up the voltage regulator circuit to supply power for the bridge. In order to the voltage adapt to the A/D converter, the voltage is amplified by opamp B, and the magnification can be adjusted through resistor R11.Fig. 2 Gas concentration signal acquisition circuitFig. 3 Temperature compensation circuitTemperature compensation circuit. The resistance of Rs is greatly affected by temperature. In order to improve system accuracy, the results must be temperature compensated or temperature correction.In system, using temperature sensor DS1820 to collect temperature signal, and using software method for temperature correction.Wireless transmission module. Wireless transceiver is achieved by a single-chip RF transceiver nRF905. MCU and nRF905 realize data and commands interaction through the SPI interface.The typical applica tion schematic is shown in Figure 4. The antenna part is 50Ω single-ended antenna.The communication frequency is 433MHz, and operating voltage is3.3V. The value of resistors,capacitors and inductor is determined by the datasheet of nRF905. GSM short message unit. The interface circuit of TC35i and MCU is shown in Figure 5. The communication between MCU and TC35i is via serial, and the rate is 9600bps. Communicationsmode is 8-bit asynchronous with a start bit, 8 data bits, and 1 stop bit. But the serial input of TC35i requires CMOS level, and serial output of 89C52 requires TTL level. In order to achieve the voltage conversion the system use the way of resistors sharing voltage. Fig. 4 nRF905 Application SchematicFig. 5 TC35i and MCU interface circuitSoftware DesignThe software system includes data acquisition module, temperature compensation module, and wireless transceiver moduleWireless sending program. NRF905 data sending process is as follows:1) When having data to send, the microcontroller send the receiver's address and the data to nRF905 chronologically by the SPI interface.Then placed the data to be transmitted into TxBuf register, send WTP command to write the data to TX-Payload register, and send WTA command to write TX address to the TX-Address register.2) The microcontroller set TRX_CE=1 and TX_EN=1 to stimulate nRF905 ShockBurstTM sending mode. When data transmission completed, the data ready pin is set high;3) Beacause of AUTO_RETRAN being high, the data of nRF905 is constantly re-issued until TRX_CE=0.4) when TRX_CE pin is set low, means the data transmission completed and nRF905 enter idlemode.Wireless receiving program. NRF905 data receiving process is as follows:1)When TRX_CE = 1 and TX_EN = 0, nRF905 enters ShockBurstTM receive modechecking constantly and waiting for receiving data.2)When nRF905 detect the carrier having same frequency band, the carrier detect pin will beset high.3)When nRF905 receive a matched address, the address matches pin will be set high.4) When packet correctly received, the word head, address and CRC bits will automatically be removed, and the data ready pin will be set high.5) MCU set TRX_CE to "0", and nRF905 enter to idle mode.6) When all the data received, nRF905 set data ready pin and address matching pin to "0", and nRF905 turn to shutdown mode or ShockBurstTM transmitmode and receive mode.Fig.6 Wireless data transmission flow chartFig.7 Wireless data receiving flow chartSummaryDesigned an equipment to detect the concentration of combustible gas, which has wireless transceiver functions and can send the alarm information to user’s mobile promptly through GSM.Experimental results show that the devices have high precision, stability and reliability. It can meet most applications which need real-time monitoring of combustible gas concentration.References[1] Liu S, Chen Q, Wang H G, eat. Electrical capacitance tomography for gas solids flow measurement for circulating fluidized beds [J].Flow Measurement and Instrumentation，2005，16(2-3):135-144.[2] TGS 813-for the Detection of Combustible Gases [DB/OL].2009-08-12.[3] Liu Wei, Chen HeXin，Zhang JunWei，etc. Intelligent control and alarm system based on TC35i. IEEE.2008 International Symposium on Computer Science and Computational Technology(ISCSCT), Shanghai, 2008:80-83Manufacturing Process and Equipment10.4028//AMR.694-697Design of Combustible Gas Detection System Using Wireless Transmission Technology 10.4028//AMR.694-697.1321译文使用无线的可燃气体检测系统的设计传输技术石家庄大学的经济学，河北，中国**************关键词：TGS813，AT89S52单片机，DS18B20，nRF905，TC35i摘要；可燃气体检测装置是在所提出的工作设计，使用无线收发器和GSM网络。