1-Multiloop PI PID controller design based on Gershgorin bands

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abplcpid控制器总结

- 针对AB PLC里的PID控制器的研究首自信热轧作业区张余海借鉴热轧1580的稀油泵站的出口压力控制，期望压力为 4.0bar，电机为异步变频电机，变频器为AB变频器，PLC和变频器的通讯通过Device Net进行数据交换。

一、控制器里的变量介绍——各变量名解释：（各变量只是显示用，他们的值时根据里面的参数设定而来）PID : PID控制器的名字（自己命名）Process Variable :过程变量的输入源设定也就是反馈值（直接连到压力反馈的输入点）Tieback:手动控制时的牵引信号，因为在手动控制中，输出（OUTPUT=SETOUTPU■是人为设定的，这个Tieback有个对应的值，也就是手动设定为0，Tieback为0，如果手动设定为100%,那么Tieback输出就是4095）具体见后面的参数设定。

Control Variable :控制变量（最关键的一个参数）的输出源设定，自己命令的一个中间变量作为转换或者直接接到给到执行器的输出信号上（例如阀的开口度、电机的转速给定）。

PID 控制器计算得到的是一个百分数，但是百分数无法输出给执行机构，必须转换成为数字量，这个控制变量（CV）就是依照对应关系转换得到的数字量（例如OUTPUT=0, CV=0，OUTPUT=100% CV=16384,具体见后面参数设定）PID Master Loop : PID的主循环，就是PID控制使用串级控制，如果是就会显示为1,如果为从就为0，但是有一个前提就是选用了串级控制（看后面的参数设定）Ihhold Bit :初始化保持位，来自1756模拟量输出通道的数据读出值，用于支持无冲击在启动，如果用户不想用此参数，可以设置为0。

In hold Value :初始化保持值，来自1756模拟量输出通道的数据读出值，用于支持无冲击在启动，如果用户不想用此参数，可以设置为0。

这两个值是为了防止系统已运行，过程变量和设定偏差太大，PID控制器输出肯定是100%，带来很大的冲击，如果设置此参数，系统先不让PID控制器工作，输出一直用In hold Value （初始化保持值），这个值可以人为的设定慢慢的变大，等到系统压力差不多达到设定压力后，然后将Ihhold Bit （初始化保持位）置0,这样系统输出就会采用PID控制器的输出了。

自动化专业英语词汇总结+汉译英

万用表
nonlinear control system
非线性控制系统
offset
偏移量、静差
open loop control
开环控制
optimal control
最优控制
orifice-plate flowmeter
孔板流量计
overshoot
超调
panel
仪表盘
pattern recognition
热电偶
threshold
阈值
time delay system
时滞系统
time-series model
时间序列模型
time-invariant system, time-varying system
定常系统/时变系统
transient process, transient response
过渡过程
热电阻Thermocouple热电偶
reverse action (direct action)
反作用，正direct action
robust control
鲁棒控制
root locus
根轨迹
sampling holder
采样保持器
saturation characteristics
饱和特性
sensor, transducer
判据
criterion
拉氏变换
laplace transform
零点
zero-point
极点
pole-point
特征方程
characteristic equation
系数
coefficient
偏差变量
deviation variable

PI控制器控制的双闭环串级调速系统的设计

目录一、PI控制器控制的双闭环串级调速系统的设计 (3)1.1 设计思路 (3)二、双闭环控制串级调速系统 (3)2.1双闭环串级调速系统 (3)2.2 串级调速时转子整流电路工作状态的选择 (4)2.3串级调速系统的动态数学模型 (6)2.4 异步电动机和转子直流回路传递函数计算 (9)2.4.1基本数据 (9)2.4.2电机和转子回路参数计算 (9)2.5调节器参数的设计- 电流环和转速环设计 (11)2.5 .1 电流环的设计 (11)2.5.2转速环的设计 (12)三、交流串级调速系统的仿真 (14)3.1 系统的仿真，仿真结果的输出及结果分析 (14)附录 (15)参考文献 (16)总结 (16)一、PI控制器控制的双闭环串级调速系统的设计1.1设计思路本次设计给定对象为某双闭环串级调速系统电机，设计时要对各环节参数计算和PI控制器的设计。

电流环按I型、转速环按Ⅱ进行整定，并对PI控制器控制的串级调速系统进行仿真。

串级调速就是在异步电机转子侧串入一个可变频、可变幅的电压。

首先，它应该是可平滑调节的，以满足对电动机转速平滑调节的要求；其次，从节能的角度看，希望产生附加直流电动势的装置能够吸收从异步电动机转子侧传递来的转差功率并加以利用。

根据以上两点要求，较好的方案是采用工作在有源逆变状态的晶闸管可控整流装置作为产生附加直流电动势的电源。

首先进行，串级调速系统的动态数学模型建立。

其次求出，转子直流回路的传递函数、异步电动机的传递函数。

最后，进行转速调节器和电流调节器的设计。

将异步电动机和转子直流回路都画成传递函数框图，再考虑转速调节器和电流调节器的给定滤波和反馈滤波环节就可直接画出双闭环串级调速系统的动态结构框图。

根据动态结构框图，在MATLAB软件中，将出双闭环串级调速系统的动态结构框图中的每一个模块用SIMULINK作出，根据求出的参数进行参数值的修改，START SIMULATION，双击示波器即可观察调速时波形的变化。

RobustControlToolbox：鲁棒控制工具箱

Model of an aircraft autopilot system (top), the algorithm used to tune it (middle), and a plot of the closed-loop response to a step setpoint and a step disturbance before and after tuning (bottom). You can use Robust Control Toolbox to automatically tune complex multivariable controllers consisting of basic Simulink blocks and then evaluate the improvement in the closed-loop response.Modeling and Quantifying Plant UncertaintyWith Robust Control Toolbox, you can capture not only the typical, or nominal, behavior of your plant, but also the amount of uncertainty and variability. Plant model uncertainty can result from:▪Model parameters with approximately known or varying values▪Neglected or poorly known dynamics, such as high-frequency dynamics▪Changes in operating conditions▪Linear approximations of nonlinear behaviors▪Estimation errors in a model identified from measured dataPlot, created by the accompanying MATLAB®code, of the worst-case gain of a system with an uncertain parameter. Robust Control Toolbox lets you create an uncertain model by adding uncertain elements to nominal plant models and then analyze the effect of uncertainty by calculating the worst-case system performance.The toolbox lets you build detailed uncertain models by combining nominal dynamics with uncertain elements, such as uncertain parameters or neglected dynamics. By quantifying the level of uncertainty in each element, you can capture the overall fidelity and variability of your plant model. You can then analyze how each uncertainelement affects performance and identify worst-case combinations of uncertain element values.Build uncertain state-space models and analyze the robustness offeedback control systems that have uncertain elements.Performing Robustness AnalysisUsing Robust Control Toolbox, you can analyze the effect of plant model uncertainty on the closed-loop stability and performance of the control system. In particular, you can determine whether your control system will perform adequately over its entire operating range, and what source of uncertainty is most likely to jeopardizeperformance.Robustness of Servo Controller for DC MotorModel uncertainty in DC motor parameters and analyze the effect of thisuncertainty on motor controller performance.You can randomize the model uncertainty to perform Monte Carlo analysis. Alternatively, you can use more direct tools based on mu-analysis and linear matrix inequality (LMI) optimization; these tools identify worst-case scenarios without exhaustive simulation.Robust Control Toolbox provides functions to assess worst-case values for:▪Gain and phase margins, one loop at a time▪Stability margins that take loop interactions into account▪Gain between any two points in a closed-loop system▪Sensitivity to external disturbancesThese functions also provide sensitivity information to help you identify the uncertain elements that contribute most to performance degradation. With this information, you can determine whether a more accurate model, tighter manufacturing tolerances, or a more accurate sensor would most improve control system robustness.Nominal and worst-case rejection of a step disturbance (top) and Bode diagram of a sensitivity function (bottom). Robust Control Toolbox lets you analyze the effect of plant model uncertainty on closed-loop stability and control system performance.Synthesizing Robust ControllersRobust Control Toolbox lets you automatically tune centralized and decentralized MIMO control systems. The controller synthesis algorithms are based on H-infinity or mu-synthesis techniques combined with nonsmooth and LMI optimization. These algorithms are applicable to SISO and MIMO control systems. MIMO controller synthesis does not require sequential loop closure, and is therefore well suited for multiloop control systems with significant loop interaction and cross-coupling.Automatic Tuning of Fixed-Structure Control SystemsMost embedded control systems have a fixed, decentralized architecture with simple tunable elements such as gains, PID controllers, or low-order filters. Such architectures are easier to understand, implement, schedule, and retune than complex centralized controllers. Robust Control Toolbox provides tools for modeling and tuning these decentralized control architectures. You can:▪Specify tunable elements such as gains, PID controllers, fixed-order transfer functions, and fixed-order state-space models▪Combine tunable elements with ordinary linear time-invariant (LTI) models to create a tunable model of your control architecture▪Specify requirements on bandwidth, loop shape, tracking performance, and disturbance rejection▪Automatically tune the controller parameters to meet requirements▪Validate controller performance in the time and frequency domainsTuning of a Two-Loop AutopilotTune a two-loop autopilot to control the pitch rate and verticalacceleration of an airframe.H-Infinity and Mu-Synthesis TechniquesRobust Control Toolbox provides several algorithms for synthesizing robust MIMO controllers directly from frequency-domain specifications of the closed-loop responses. For example, you can limit the peak gain of a sensitivity function to improve stability and reduce overshoot, or limit the gain from input disturbance to measured output to improve disturbance rejection. Using mu-synthesis algorithms, you can optimize controller performance in the presence of model uncertainty, ensuring effective performance under all realistic scenarios.H-infinity and mu-synthesis techniques provide unique insight into the performance limits of your control architecture, and let you quickly develop first-cut compensator designs.Analyzing and Tuning Controllers in SimulinkRobust Control Toolbox provides tools for performing robustness analysis and tuning of controllers modeled in Simulink.Uncertainty Modeling and Robustness AnalysisThe toolbox lets you model and analyze uncertainty in Simulink models. You can:▪Introduce uncertainty into a Simulink model by using an Uncertain State Space block or by specifying block linearization for any Simulink block▪Linearize a Simulink model to create an uncertain system that represents the whole Simulink model▪Analyze the resulting uncertain system for stability and performanceLinearization of Simulink Models with UncertaintyCompute uncertain linearizations of a Simulink model.Automatic Controller TuningRobust Control Toolbox lets you automatically tune decentralized controllers modeled in Simulink. You can:▪Specify Simulink model blocks that should be tuned▪Specify requirements on bandwidth, stability margins, tracking performance, and disturbance rejection▪Automatically tune specified blocks to meet requirements▪Validate your design by running nonlinear simulationsUsing this approach you can automatically tune complex multivariable controllers that are modeled using Simulink blocks. For example, you can automatically tune inner-loop and outer-loop PID controllers in a multiloop control system without changing the control system architecture.Tuning a Decentralized Control System for a Helicopter5:45Tune a complex flight control system for a helicopter.Reducing Plant and Controller OrderDetailed first-principles or finite-element plant models often have a large number of states. Similarly, H-infinity or mu-synthesis algorithms tend to produce high-order controllers with superfluous states. Robust Control Toolbox provides algorithms that let you reduce the order (number of states) of a plant or controller model while preserving its essential dynamics. As you extract lower-order models, which are more cost effective to implement, you can control the approximation error.Product Details, Demos, and System Requirements/products/robustTrial Software/trialrequestSales/contactsalesTechnical Support/support Bode plots comparing magnitude and phase of the original and reduced-order models for the rigid body motion dynamics of a multistory building.The model reduction algorithms are based on Hankel singular values of the system, which measure the energy of the states. By retaining high-energy states and ignoring low-energy states, the reduced model preserves the essential features of the original model. You can use the absolute or relative approximation error to select the order, and use frequency-dependent weights to focus the model reduction algorithms on specific frequency ranges.Simplifying Higher-Order Plant ModelsApproximate high-order plant models with simpler, lower-order models.ResourcesOnline User Community /matlabcentral Training Services /training Third-Party Products and Services /connections Worldwide Contacts /contact。

MULTIPROG PID相关功能块

FPID.INTLCKV(REAL)
FPID.Yout(REAL) PID.XOUT(REAL)
PID.Enable(BOOL)
时起作用本地设定点（SV），当 REMOTE=FALSE 时起作用过程值（PV）比例常数（K），无单位
积分时间常数（单位秒）
微分时间常数（单位秒）
控制器输出的上限控制器输出的下限内部互锁值，当 INTLCK=TRUE 时， Yout 等于此值调节值（输出值 MV）
和模拟量输出模块 ADAM-5024 的输出有关联当一个周期信号将控制此 PID 功能块的执行时，可能会使用这个输入参数
2、单回路控制系统中调节器正反作用的选择
任何一个控制系统在投运前，必须正确选择调节器的正反作用，使控制作用的方向对头，否则，在闭合回路中进行的不是负反馈而是正反馈，它将不断增大偏差，最终必将把被控变量引导到受其他条件约束的高端或低端极限值上。
负号
气开气关
正作用反作用
3、 PID控制例子
使用 ADAM-5510KW 进行温度 PID 控制的一个例程，控制对象是温度箱的温度。
ADAM-5024 第 0 通道固定输出 10V 电压控制固态继电器加热水泥电阻。 ADAM-5018 第 0 通道，用 K 型热电偶，采集水泥电阻的温度做 PV 值。 ADAM-5024 第 3 通道输出 0-10V 电压，通过控制风扇的转速通过降温来控制温度箱的温度。 PID 作用是反作用控制，采用 FPID 功能块。程序在 Default Task 下实现如下：
远程(TRUE)或本地(FALSE)设定点之
间的开关
FPID.AUTO(BOOL)
自动(TRUE)或手动(FALSE)控制之间

三菱PLCPID调节手册

Programming ManualMitsubishi Programmable Logic ControllerQCPU(Q Mode)/QnACPU(PID Control Instructions)• SAFETY CAUTIONS •(You must read these cautions before using the product)In connection with the use of this product, in addition to carefully reading both this manual and the related manuals indicated in this manual, it is also essential to pay due attention to safety and handle the product correctly.The safety cautions given here apply to this product in isolation. For information on the safety of the PC system as a whole, refer to the CPU module User's Manual.Store this manual carefully in a place where it is accessible for reference whenever necessary, and forward a copy of the manual to the end user.REVISIONS* The manual number is given on the bottom left of the back cover.Print Date* Manual Number RevisionDec., 1999SH (NA) 080040-A First editionJun., 2001SH (NA) 080040-B Partial additionAbout Manuals, Chapter 1, Chapter 2, Section 2.1, 3.1, 3.2, 3.3, 3.3.1,4.2.3, 4.3.2, 4.3.5, Chapter 5, Section5.1, 5.2, Chapter 6, Chapter 7,Section 8.1, 8.2Japanese Manual Version SH-080022-BThis manual confers no industrial property rights or any rights of any other kind, nor does it confer any patent licenses. Mitsubishi Electric Corporation cannot be held responsible for any problems involving industrial property rights whichmay occur as a result of using the contents noted in this manual.1999 MITSUBISHI ELECTRIC CORPORATIONINTRODUCTIONThank you for choosing the Mitsubishi MELSEC-Q/QnA Series of General Purpose Programmable Controllers. Please read this manual carefully so that the equipment is used to its optimum. A copy of this manual should be forwarded to the end User.CONTENTS1. GENERAL DESCRIPTION 1 – 1 to 1 - 21.1 PID Processing Method...........................................................................................................................1 - 22. SYSTEM CONFIGURATION FOR PID CONTROL 2 - 1 to 2 - 22.1 Applicable PLC CPU................................................................................................................................2 - 13. PID CONTROL SPECIFICATIONS 3 - 1 to 3 - 63.1 Performance Specifications.....................................................................................................................3 - 1 3.2 Operation Expressions.............................................................................................................................3 - 1 3.3 PID Control Instruction List......................................................................................................................3 - 23.3.1 How to read the instruction list..........................................................................................................3 - 33.3.2 PID operation instruction list.............................................................................................................3 - 54. PID CONTROL 4 - 1 to 4 - 124.1 Outline of PID Control..............................................................................................................................4 - 1 4.2 PID Control...............................................................................................................................................4 - 24.2.1 Operation method..............................................................................................................................4 - 24.2.2 Normal operation and reverse operation..........................................................................................4 - 24.2.3 Proportionate operation (P operation)..............................................................................................4 - 44.2.4 Integrating operation (I operation)....................................................................................................4 - 54.2.5 Differentiating operation (D operation).............................................................................................4 - 64.2.6 PID operation.....................................................................................................................................4 - 7 4.3 PID Control Functions..............................................................................................................................4 - 74.3.1 Bumpless changeover function.........................................................................................................4 - 74.3.2 MV higher/lower limit control function...............................................................................................4 - 84.3.3 Monitorning PID control with the AD57(S1) (QnACPU only)...........................................................4 - 94.3.4 Function for transfer to the SV storage device for the PV in manual mode..................................4 - 104.3.5 Changing PID Control Data or input/output Data Setting Range(High Performance model QCPU Only).........................................................................................4 - 11 5. PID CONTROL PROCEDURE 5 - 1 to 5 - 105.1 PID Control Data......................................................................................................................................5 - 35.1.1 Number of loops to be used and the number of loops to be executed in a single scan.................5 - 65.1.2 Sampling cycle..................................................................................................................................5 - 7 5.2 Input/Output Data.....................................................................................................................................5 - 86. PID CONTROL INSTRUCTIONS 6 - 1 to 6 - 27. HOW TO READ EXPLANATIONS FOR INSTRUCTIONS7 - 1 to 7 - 28. PID CONTROL INSTRUCTIONS8 - 1 to 8 - 108.1 PID Control Data Settings.........................................PIDINIT,PIDINITP................................................8 - 2 8.2 PID Control ...............................................................PIDCONT,PIDCONTP.........................................8 - 3 8.3 Monitoring PID Control Status (QnACPU only).......PID57,PID57P......................................................8 - 5 8.4 Operation Stop/Start of Designated Loop No..........PIDSTOP,PIDSTOPP,PIDRUN,PIDRUNP.........8 - 8 8.5 Parameter Change at Designated Loop...................PIDPRMW,PIDPRMWP......................................8 - 99. PID CONTROL PROGRAM EXAMPLES9 - 1 to 9 - 109.1 System Configuration for Program Examples.........................................................................................9 - 1 9.2 Program Example for Automatic Mode PID Control...............................................................................9 - 2 9.3 Program Example for Changing the PID Control Mode between Automatic and Manual....................9 - 6APPENDIX APP - 1APPENDIX 1 PROCESSING TIME LIST................................................................................................APP – 1About ManualsThe following manuals are also related to this product.In necessary, order them by quoting the details in the tables below. Related ManualsManual Name Manual Number (Model Code)High Performance model QCPU (Q mode) User's Manual(Function Explanation/Program Fundamentals)Describes the functions, programming procedures, devices, parameter types and program types necessary in program creation using QCPU (Q mode).(Option)SH-080038 (13JL98)QnACPU Programming Manual (Fundamentals)Describes how to create programs, the names of devices, parameters, and types of program.(Option)IB-66614 (13JF46)QCPU (Q mode) /QnACPU Programming Manual (Common Instructions)Describes how to use sequence instructions, basic instructions, and application instructions.(Option)SH-080039 (13JF58)QnACPU Programming Manual (Special Function)Describes the dedicated instructions for special function modules available when using theQ2ACPU(S1), Q3ACPU, and Q4ACPU.(Option)SH-4013 (13JF56)QnACPU Programming Manual (AD57 Instructions)Describes the dedicated instructions for controlling an AD57(S1) type CRT controller module available when using the Q2ACPU(S1), Q3ACPU, or Q4ACPU.(Option)IB-66617 (13JF49)QCPU (Q mode) / QnACPU Programming Manual (SFC)Describes the system components, performance specifications, and functions, protramming, debugging and error codes of MELSAP-3(Option)SH-080041 (13JF60)Q4ARCPU Programming Manual (Application PID Edition)Describes the programming procedures and device name necessary in program creation to control Applied PID using process control instructions.(Option)IB-66695 (13JF52)Before reading this manual, refer to High Performance model QCPU (Q mode) User'sManual (Function Explanation/Programming Fundamentals) and QnACPUProgramming Manual (Fundamentals) in order to confirm the programs, I/Oprocessing, and devices used with High Performance model QCPU(Q mode)/QnACPU.Describes the instructionsused for Applied PIDcontrol.Generic Names:High Performance model QCPU...Generic names for Q02CPU, Q02HCPU, Q06HCPU, Q12HCPU, Q25HCPU QnACPU ........................................Generic names for Q2ASCPU, Q2ASCPU-S1, Q2ASHCPU, Q2ASHCPU-S1, Q2ACPU, Q3ACPU, Q4ACPU, Q4ARCPUCPU module....................................Generic names for QnACPU, High Performance model QCPU1. GENERAL DESCRIPTION1 This manual describes the sequence program instructions used to execute PID controlwith the High Performance model QCPU/QnACPU.The High Performance model QCPU /QnACPU has the capability to use instructionsfor PID control as a standard feature, so PID control can be executed by loading anA/D conversion module and a D/A conversion module.In addition, the PID control status can be monitored with an AD57(S1).POINTThe Basic model QCPUs (Q00JCPU, Q00CPU, Q01CPU) are not compatible withthe PID control instructions.Use the High Performance model QCPU to use the PID control instructions.REMARKThe High Performance model QCPU is the generic term of the Q02CPU, Q02HCPU,Q06HCPU, Q12HCPU and Q25HCPU.Any of them is abbreviated to the High Performance model QCPU in this manual.1.1 PID Processing MethodThis section describes the processing method for PID control using PID controlinstructions. (For details on PID operations, see Chapter 4.)Execute PID control with PID control instructions by loading an A/D conversion moduleand a D/A conversion module, as shown in Figure 1.1.As shown in Figure 1.1, using the previously set SV (set value) and the digital PV(process value), which is read from the A/D conversion module, PID operation isexecuted to obtain the MV (manipulated value).The calculated MV (manipulated value) is output to the D/A conversion module.The sampling cycle is measured, and the PID operation is performed, when thePIDCONT instruction is executed in the sequence program, as illustrated below.PID operation in accordance with the PIDCONT instruction is executed in presetsampling cycles.MELSEC-Q/QnA2. SYSTEM CONFIGURATION FOR PID CONTROL22. SYSTEM CONFIGURATION FOR PID CONTROLThis section describes the system configuration for PID control using PID control instructions.(For details on the units and modules that can be used when configuring the system, refer to the manual for the CPU module used.)CRTOperation panelD/A conversion moduleA/D conversion moduleMain base unitExtension cableExtension base unitPV (process value) inputFor MV (manipulated value) outputFor PID control monitoring (Only QnACPU)CRT control module AD57 or AD57-S1 onlyQnACPUQCPU High Performance modelPOINT(1) For QnACPU, the reference range for SV, PV, and MV values used in PID operations is 0 to 2000. If the resolution of the A/D conversion module or D/Aconversion module used for input/output in PID control is not 0 to 2000, convert the digital values to 0 to 2000.(2) For High Performance model QCPU, a setting is selectable from fixed values as described in (1) or any appropriate values for the unit used. See Section 4.3.5for details.2.1 Applicable PLC CPUComponent ModuleHigh Performance model QCPU Q02CPU, Q02HCPU, Q06HCPU, Q12HCPU, Q25HCPUQnACPUQ2ASCPU, Q2ASCPU-S1, Q2ASHCPU, Q2ASHCPU-S1Q2ACPU, Q3ACPU, Q4ACPU, Q4ARCPU2. SYSTEM CONFIGURATION FOR PID CONTROLMELSEC-Q/QnA MEMO33. PID CONTROL SPECIFICATIONSThis section gives the specifications PID control using PID control instructions.3.1 Performance SpecificationsThe performance specifications for PID control are tabled below.SpecificationQnACPUItemWith PID Limits for HighPerformance modelQCPU Without PID Limits forHigh Performance modelQCPUNumber of PID control loops—32 loops (maximum)Sampling cycle T S 0.01 to 60.00 sPID operation method—Process value differentiation (normal operation/reverse operation)Proportionate constant K P 0.01 to 100.00Integration constant T I 0.1 to 3000.0 s PID constant setting rangeDifferential constantT D 0.00 to 300.00 sSV (set value) setting range SV 0 to +2000-32768 to +32767PV (process value) setting range PV MV (manipulated value) output range MV-50 to +2050-32768 to +327673.2 Operation ExpressionsThe operation expressions for PID control using PID control instructions are indicated below.NameOperation ExpressionsMeanings of SymbolsNormal operationEV n =PV nf *-SVMV n = MV MV=K p {(EV n -EV n-1)+ EV n - (2PV nf-1-PV nf -PV nf-2)}T S T I T DT SProcess valuedifferentiationReverse operationEV n =SV-PV nf *MV n = MVMV=K p {(EV n -EV n-1)+ EV n + (2PV nf-1-PV nf-PV nf-2)}T ST I T D T S EV n : Deviation in the present sampling cycle EV n-1: Deviation in the preceding sampling cycleSV : Set valuePV nf : Process value of the present sampling cycle (after filtering)PV nf-1: Process value of the preceding samplingcycle (after filtering)PV nf-2: Process value of the sampling cycle two cycles before (after filtering)MV : Output change amount MV n : Present manipulation amount K P : Proportionate constant T S: Sampling cycle T I : Integration constantT D: Differential constant POINT(1) *:PV nf is calculated using the following expression.Therefore, it is the same as the PV (process value) of the input data as long as the filter coefficient is not set for the input data.Process Value after Filtering PV nf = PV n + (PV nf -1-PV n )PV n : Process value of the present sampling: Filter coefficientPV nf-1: Process value of the preceding sampling cycle (after filtering)(2) PV nf is stored in the I/O data area. (See Section 5.2)3.3 PID Control Instruction ListA list of the instructions used to execute PID control is given below.CPU Instruction Name Processing DetailsQ QnAPIDINIT Sets the reference data for PID operation.*1PIDCONT Executes PID operation with the SV (set value) and the PV (process value).*1PID57Used to monitor the results of PID operation at an AD57(S1).×PIDSTOP PIDRUN Stops or starts PID operation for the set loop No.PIDPRMWChanges the operation parameters for the designated loop number to PID control data.*1: For High Performance model QCPU, PID limits can be set to ON or OFF. SeeSections 5.1 and 5.2 for the setting range used in each mode.3.3.1 How to read the instruction listThe instruction list in Section 3.3.2 has the format indicated below:Table 3.1 How to Read the Instruction ListExplanation(1) Classification of instructions according to their application.(2) Instruction names written in a sequence program.(3) Symbols used in the ladder diagram.(4) Processing for each instruction.(5) The execution condition for each instruction. Details are given below.(6) Number of instruction stepsFor details on the number of steps, refer to the QCPU (Q mode) /QnACPU Programming Manual (Common Instructions).(7) A circle indicates that subset processing is possible.For details on subset processing, refer to the QCPU (Q mode) /QnACPU Programming Manual (Common Instructions).(8) Indicates the page number in this manual where a detailed description for theinstruction can be found.3.3.2 PID operation instruction list4.2 PID ControlThe operation methods for PID control with the PID control instructions are the speedmethod and process value differentiation method. The following describes the controlexecuted for both of these methods:4.2.1 Operation method(1) Speed method operationThe speed method operation calculates amounts of changes in the MVs(manipulated values) during PID operation.The actual MV is the accumulatedamount of change of the MV calculated for each sampling cycle.(2) Process value differentiation method operationThe process value differentiation method operation executes PID operations bydifferentiating the PV (process value).Because the deviation is not subject to differentiation, sudden changes in theoutput due to differentiation of the changes in the deviation generated bychanging the set value can be reduced.Either forward operation or reverse operation can be selected to designate thedirection of PID control.4.2.2 Normal operation and reverse operation(1) In normal operation, the MV (manipulated value) increases as the PV (processvalue) increases beyond the SV (set value).(2) In reverse operation, the MV (manipulated value) increases as the PV (processvalue) decreases below the SV (set value).(3) In normal operation and reverse operation, the MV (manipulated value) becomeslarger as the difference between the SV (set value) and the PV (process value)increases.(4) The figure below shows the relationships among normal operation and reverseoperation and the MV (manipulated value), the PV (process value), and the SV(set value):(5) The figure below shows examples of process control with normal operation andreverse operation:4.2.3 Proportionate operation (P operation)The control method for proportionate operation is described below.(1) In proportionate operation, an MV (manipulated value) proportional to thedeviation (the difference between the set value and process value) is obtained.(2) The relationship between E (deviation) and the MV (manipulated value) isexpressed by the following formula:MV=Kp • EKp is a proportional constant and is called the "proportional gain".(3) The proportionate operation in step response with a constant E (deviation) isillustrated in Fig. 4.2.(4) The MV (manipulated value) changes within the range from -50 to 2050 or theuser-defined range (for High Performance model QCPU only).The MV (manipulated value) in response to the same deviation becomes largeras Kp becomes larger, thus the compensating motion is greater.(5) The proportionate operation is always associated with an offset (offset error).4.2.4 Integrating operation (I operation)The control method for integrating operation is described below.(1) In the integrating operation, the MV (manipulated value) changes continuously tozero deviation when it occurs.This operation can eliminate the offset that is unavoidable in proportionateoperation.(2) The time required for the MV in integrating operation to reach the MV forproportionate operation after the generation of deviation is called the integratingtime. Integrating time is expressed as T I.The smaller the setting for T I, the more effective the integrating operation will be.(3) The integrating operation in step response with a constant E (deviation) isillustrated in Fig. 4.3.(4) Integrating operation is always used in combination with proportionate operation(PI operation) or with proportionate and differentiating operations (PID operation).Integrating operation cannot be used independently.4.2.5 Differentiating operation (D operation)The control method for differentiating operation is described below.(1) In differentiating operation, an MV (manipulated value) proportional to thedeviation change rate is added to the system value to zero deviation when itoccurs.This operation prevents significant fluctuation at the control objective due toexternal disturbances.(2) The time required for the MV in the differentiating operation to reach the MV forthe proportionate operation after the generation of deviation is called thedifferentiating time. Differentiating time is expressed as T D.The smaller the setting for T D, the more effective the differentiating operation willbe.(3) The differentiating operation in step response with a constant E (deviation) isillustrated in Fig. 4.4.(4) Differentiating operation is always used in combination with proportionateoperation (PD operation) or with proportionate and integrating operations (PIDoperation).Differentiating operation cannot be used independently.4.2.6 PID operationThe control method when proportionate operation (P operation), integrating operation (Ioperation), and differentiating operation (D operation) are used in combination isdescribed below.(1) During PID operation, the system is controlled by the MV (manipulated value)calculated in the (P + I + D) operation.(2) PID operation in step response with a constant E (deviation) is illustrated in Fig.4.5.4.3 PID Control FunctionsDuring PID control using the PID control instructions, MV upper/lower limit control isautomatically executed by the bumpless changeover function explained below.4.3.1 Bumpless changeover functionThis function controls the MV (manipulated value) continuously when the control modeis changed between manual and automatic.When the control mode is changed between manual and automatic, data is transmittedbetween the MV area for automatic mode and the MV area for manual mode.The control mode is changed in the input/output data area (see Section 5.2).(1) Changing from the manual ...........mode to the automatic mode The MV in the manual mode is transmitted to the MV area for the automatic mode.(2) Changing from the automatic .......mode to the manual mode The MV in the automatic mode is transmitted to the MV area for the manual mode.POINT(1) Manual and automatic modes of PID control:1) Automatic modePID operation is executed with a PID control instruction.The control object is controlled according to the calculated MV.2) Manual modePID operation is not executed. The MV is calculated by the user and thecontrol object is controlled according to the user-calculated MV.(2) The loop set in the manual mode stores the PV (process value) in the set valuearea every sampling cycle.4.3.2 MV higher/lower limit control functionThe MV higher/lower limit control function controls the higher or lower limit of the MVcalculated in the PID operation. This function is only effective in the automatic mode. Itcannot be executed in the manual mode.By setting the MV higher limit (MVHL) and the MV lower limit (MVLL), the MVcalculated in the PID operation can be controlled within the range between the limits.When the MV higher/lower limit control function is used, the MV is controlled asillustrated above.A MVHL (manipulated value higher limit) and MVLL (manipulated value lower limit)takes on a value between -50 and 2050 or a user-defined value (for High Performancemodel QCPU only).The following are the default settings:• Higher limit................2000 (Or user-defined value)• Lower limit................0 (Or user-defined value)The value set for the higher limit must not be smaller than the value set for the lowerlimit.An error will occur if it is.4.3.3 Monitoring PID control with the AD57(S1) (QnACPU only)The PID control operation results can be monitored in a bar graph with an AD57(S1)CRT controller unit.(1) The monitor screen displays the monitored information of eight loops beginningwith the designated loop number.POINTThe SV, PV, and MV present value are displayed as percentages of 2000.1) SV percentage display...............SV2000100 (%)2) PV percentage display...............PV2000100 (%)3) MV percentage display...............MV2000100 (%)(2) Use the PID57 instruction to execute monitoring with an AD57(S1).See Section 8.3 for details on the PID57 instruction.4.3.4 Function for transfer to the SV storage device for the PV in manual modeThe PIDCONT instruction is also executed in manual mode.In the manual mode, it ispossible to select whether or not the PV input from the A/D conversion module onexecution of the PIDCONT instruction is transferred to the SV storage device or not inaccordance with the ON/OFF status of the PID bumpless processing flag (SM774).• When SM774 is OFF : When the PIDCONT instruction is executed, the PV istransferred to the SV storage device.On switching from the manual mode to the automaticmode, the MV output is continued from the value in themanual mode.After switching to the automatic mode, control can beswitched from the MV that was being output to the SV bychanging the SV.• When SM774 is ON : When the PIDCONT instruction is executed, the PV is nottransferred to the SV storage device.On switching from the manual mode to the automaticmode, control can be switched from the MV output in themanual mode to the SV.Before switching to the automatic mode, store a SV in theSV storage device.POINTWhen SM774 is ON or OFF, switching from the manual mode to the automaticmode may cause different control effects as follows.• When SM774 is OFF, the PV is transferred to the SV storage device.When the manual mode is switched to the automatic mode, no difference iscaused between the PV and the SV and the MV does not change rapidly, exceptthat the SV differs from a target value defined in the automatic mode.Use the sequence program to make step-by-step adjustments to the SV so thatthe SV approaches closer to the target value.See sample programs in Section 9.3.• When SM774 is ON, the PV is not transferred to the SV storage device. This maycause a difference between the PV and the SV when the manual mode isswitched to the automatic mode.A greater difference may cause the MV to change rapidly. So this procedure isused for systems in which the manual mode can be switched to the automaticmode only when the PV approaches closer tothe SV.The automatic mode can be effected without using the sequence program tomake step-by-step adjustments to the SV.REMARKThe SV and PV are stored in the devices in the I/O data area designated by thePIDCONT instruction.4.3.5 Changing the PID Control Data or Input/Output Data Setting Range (HighPerformance model QCPU Only)For High Performance model QCPU, setting ranges can be selectable for PID controldata (see Section 5.1) and input/output data (see Section 5.2). To effect the user-defined setting range, designate the loops for which PID limit settings (SD774 and SD775) are defined, and then set these loops' bits to ON before executing the PIDCONTand PIDINT instructions.SD774SD7750 : PID Limit ON (default setting)1 : PID Limit OFF (user-defined setting)A "PID Limit OFF" setting does not effect the limit control over internal data. To effectthe limit control, execute the processing by operating from the user's application side.。

步进电机模糊pid算法基本原理,c语言实现

步进电机模糊pid算法基本原理,c语言实现模糊PID（Proportional-Integral-Derivative）控制算法结合了模糊逻辑和传统PID控制算法，旨在提高系统的鲁棒性和稳定性。

步进电机作为一种常见的执行器，可以通过模糊PID算法实现精确的位置控制。

以下是模糊PID算法的基本原理以及C语言实现的简要步骤：模糊PID算法基本原理：1.模糊化输入和输出：将系统的输入（误差）和输出（控制量）进行模糊化，将其转换为模糊集合。

2.模糊规则库：建立模糊规则库，其中包含了一系列模糊规则，用于描述输入与输出之间的关系。

这些规则可以根据经验知识或系统模型来确定。

3.模糊推理：通过模糊规则库对模糊化的输入进行推理，得到模糊输出。

通常采用最大最小原则或加权平均等方法进行推理。

4.去模糊化：将模糊输出转换为确定性的控制量，即进行去模糊化操作。

常用的方法包括最大隶属度法、加权平均法等。

5.PID调节器：利用模糊输出和经典PID控制算法相结合，调节系统的控制量，使系统达到期望的运行状态。

C语言实现步骤：1.模糊化输入和输出：定义输入误差和输出控制量的模糊集合，并实现模糊化函数。

2.模糊规则库：定义一系列模糊规则，描述输入和输出之间的关系。

3.模糊推理：根据输入误差和模糊规则库进行推理，得到模糊输出。

4.去模糊化：实现去模糊化函数，将模糊输出转换为确定性的控制量。

5.PID调节器：结合经典PID控制算法，根据模糊输出和去模糊化后的控制量进行调节。

以下是一个简单的C语言实现示例：// 模糊化函数float fuzzyfication(float error) {// 省略具体实现，根据误差值计算归属度return fuzzy_value;}// 模糊规则库float fuzzy_rule(float error) {// 省略具体实现，定义模糊规则return fuzzy_output;}// 去模糊化函数float defuzzyfication(float fuzzy_output) {// 省略具体实现，根据模糊输出计算确定性的控制量return control_output;}int main() {float error = 0.0; // 输入误差float fuzzy_input = fuzzyfication(error); // 模糊化输入float fuzzy_output = fuzzy_rule(fuzzy_input); // 模糊推理float control_output = defuzzyfication(fuzzy_output); // 去模糊化输出// 利用确定性的控制量进行PID调节// 省略PID控制算法的实现// 控制步进电机运动return 0;}在实际应用中，模糊PID算法需要根据具体的系统和需求进行调试和优化，以实现良好的控制效果。

测量词汇

测量词汇4
测量词汇1
2006-6-18 9:44
页面功能【字体：大中小】【打印】【关闭】
modeling，建模
modern control theory，现代控制理论
modern polarography，近代极谱法
modifiability，可修改性
（measure）target，（被测）目标
measured alue，被测值
（measuring）potentiometer，（测量）电位差计
（measuring）transducer，（测量）传感器
2006-6-18 9:45
页面功能【字体：大中小】【打印】【关闭】
moisture sensor，湿敏元件
moiving-iron instrument，动铁式[电磁系）仪表
molecular absorption spectrometry，分子吸收光谱法
molecular beam mass spectrometer，调制分子束质谱计
modulator-demodulator；modem，调制解调器
module，模块
modulus of elasticity，弹性模量
moire frenge grating，莫尔条纹光栅
moire fringe，莫尔条纹
moisture content，含湿量；水汽含量
mulit-stage accelerating electron gun，多极加速电子枪
multi band seismograph，多频带地震仪
multi collectors mass spectrometer，多接收器质谱计

PSL-603U调试手册(智能站)国网版本V1.0

工具软件名称 SGVIEW UpdateTool VSCL61850 PS61850 CONNER SACWaveAnalysis
版本 V3.60 V1.28 V4.10 V4.10 V2.60 使用低版本工具！！
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工具软件版本更新请关注工程技术部发布网站： http://jv-s-sp/rd/TSrelease
文档版本 V1.0
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修订日期 20术部
PSL-603U 智能站调试手册
目录版本说明.......................................................................................................................................................................................................... - 2 目录................................................................................................................................................................................................................ - 3 1. 现场信息确认.....................................................................................

英文文献总结

E1.Robust Global Trajectory Tracking for Underactuated VTOL Aerial Vehicles using Inner-Outer Loop Control ParadigmsSOURCE：IEEE TRANSACTIONS ON AUTOMATIC CONTROL现有的姿态-位置双闭环稳定控制的思路是通过独立的调节各环节参数实现系统稳定。

但是这一类方法需要控制对象的先验知识，并且在实际使用过程中并不是那么地有效率，因为外界干扰和参数摄动的影响都是不确定的。

为了解决这一方面的限制，提出了不需要对控制对象的动力学模型的先验知识的一种方法。

此方法是结合线性反馈律和前馈律的姿态控制器，提出的此控制器更有利于工程实现。

另外文中使用了SO(3)（李群三维旋转群）对飞行器的坐标系进行了描述。

E2.Robust global trajectory tracking for a class of underactuated vehicles SOURCE：Automatica本文提出解决了具有完全扭矩驱动和单一方向推力的这种特定类别的欠驱动飞行器的轨迹跟踪的问题。

在某些给定的假设下，提出的控制律能够跟踪平滑的参考位置轨迹，同时保证和期望姿态的角度偏差最小。

该方法在有界状态干扰的情况下可以全局地实现，即在不考虑飞行器的初始状态。

所提出的控制器在实验中使用小规模四旋翼飞行器进行测试。

文中利用混合四元数反馈策略为飞行器设计控制器。

同时，在此控制器中提出了对静态加速度扰动具有鲁棒性的积分项，并使用鲁棒的混合系统提取期望的单元四元数，并进行试验进行验证。

此文也是使用SO(3)（李群三维旋转群）对飞行器的坐标系进行了描述。

E3.Dynamics Modeling and Trajectory Tracking Control of a Quadrotor Unmanned Aerial VehicleSOURCE：Journal of Dynamic Systems, Measurement, and Control文中介绍的飞行器轨迹跟踪的功能。

电力电子外文摘要综述翻译

综述1、Modeling, Control, and Implementation of DC–DC Converters for Variable Frequency Operation频率可变的DC-DC变换器的建模，和实现Abstract—In this paper, novel small-signal averaged models for dc–dc converters operating at variable switching frequency are derived. This is achieved by separately considering the on-time and the off-time of the switching period. The derivation is shown in detail for a synchronous buck converter and the model for a boost converter is also presented. The model for the buck converter is then used for the design of two digital feedback controllers, which exploit the additional insight in the converter dynamics. First, a digital multiloop PID controller is implemented, where the design is based on loop-shaping of the proposed frequency-domain transfer functions. And second, the design and the implementation of a digital LQG state-feedback controller, based on the proposed time-domain state-space model, is presented for the same converter topology. Experimental results are given for the digital multiloop PID controller integrated on an application-specified integrated circuit in a 0.13μmCMOS technology, as well as for the statefeedback controller implemented on an FPGA. Tight output voltage regulation and an excellent dynamic performance is achieved, as the dynamics of the converter under variable frequency operation are considered during the design of both implementations.本文中利用小信号的平均值通过变频开关实现DC-DC的变换，通过单独控制导通和关断时间，并建立了back拓扑模型和boost拓扑模型，该模型的buck转换器用于两个数字反馈控制器，实现变换器的动态控制。

电气自动化专业词汇

1常用专业词汇表0 型系统type 0 system1 型系统type 1 system2 型系统type 2 systemW 平面w-planeZ 变换z-transformZ 传递函数z-transfer functionZ 平面z-planeZ 域z-domain安全系数safety factor按钮push bottom, press-button靶式流量变送器target flow transmitter白箱测试法white box testing approach 白噪声white noise半导体可控整流器，可控硅semiconductor controlled rectifier(SCR)半径radius(复数为 radii)半实物仿真semi-physical simulation半自动化semi-automation 保险丝fuse被控/控制对象controlled plant被控/受控变量controlled variable比冲specific impulse比例积分微分控制器，PID控制器proportionalplusintegralplusderivativecontroller 比特，二进制的一位bit闭环传递函数closed loop transfer function闭环极点closedlooppole闭环控制系统closed loop control system 闭环零点closedloopzero闭环增益closedloopgain 编码encode编码器，编码装置coder编译程序，编译器compiler变换矩阵transformation matrix变结构控制系统variable structure control system变频电气传动variable frequency electric drive变送器，发射机transmitter 标记sentinel标识符identifier表压力gage pressure 并联电抗器shunt reactor 并联电容器shunt capacitor 伯德图Bode diagram不间断电源uninterruptible power supply(UPS)不间断工作制，长期工作制uninterrupted duty步进电机stepping/stepper/step motor 步进电气传动stepmotion electric drive步进控制step/step-by-step control采样频率sample frequency采样系统sampling system参数，参量parameter操作流程图operating flow chart 测量围measuring range测试信号test signal策略函数strategic function差动放大器differential amplifier差压控制器differential pressure controller 场效应晶体管field effect transistor(FET)超声厚度计ultrasonicthicknessmeter超声流量计ultrasonic flowmeter超声物位计ultrasonic levelmeter 称重传感器weighingcell城市规划urban planning程序设计员programmer弛振荡器relaxation oscillator初始电压initial voltage初始条件initial condition触发器flip-flop穿越频率，交越频率cross-over frequency传递函数矩阵transfer function matrix 传递函数模型transfer function model 传感器sensor, transducer传输延迟transport lag串级控制cascade control串级系统cascade system串联补偿cascade/series compensation串行的，连续的serial磁存储器magnetic storage磁道track磁极magnetic pole磁力矩magnetic moment 磁盘disc, disk磁头臂，存取臂access arm磁心存储器core storage, core store磁滞现象hysteresis次优控制suboptimal control 次优系统suboptimalsystem 次优性suboptimality从站slave station粗调coarse adjustment存储单元memory cell/location 存储器memory, storage存取时间access time打印机printer 打印输出printout 代码，编码code单变量控制系统single variable control system单端谐振变换器single-ended resonant converter单环协调策略single loop coordination strategy 单回路控制器single loop controller单回路控制系统single loop control system单级过程single level process单结晶体管unijunction transistor(UJT)单输入单输出控制系统single input single output control system(SISO)单位反馈unit feedback单位阶跃函数unit step function 单位圆unit circle单相整流single-phase rectification单元测试unit testing单值非线性single value nonlinearity单自由度陀螺仪single degree of freedom gyro等待时间latency time低纹波low-ripple地线earth lead/wire, ground wire/leak地址address电传打字机teleprinter电磁阀solenoid valve 电感器inductor电机motor电力传输power transmission 电力电子学powerelectronics 电流表，安培计ammeter电流互感器current transformer电流源逆变器current-source inverters(CSI) 电路，线路circuit电气系统electric system电容器capacitor, condenser, nichicon电容量，电容capacity电枢绕组armature winding/coil电刷brush电压调节器voltage regulator电压互感器voltage transformer电压降voltage/potential drop 电压上升率rate-of-rise ofvoltage电压源逆变器voltage-source inverters(VSI) 电远传压力表transmissiblepressuregauge 电阻resistance电阻器resistor阻抗，全电阻impedance调试debugging, troubleshoot 调速系统speed control system调用指令call instruction定常/非时变/时不变系统time-invariant system定点精[确]度stationaccuracy定理证明theorem proving定时timing定子stator动圈式仪表moving coil meter 动态控制dynamiccontrol 动态偏差dynamic deviation动态响应dynamic response短路保护short-circuit protection短期工作制short time duty短期计划short term planning短期记忆short term memory(SIM) 断路器circuit breaker队决策理论team decision theory 队论team theory多回路控制multiloop control额定电流current rating/rated current 额定电压voltage rating/rated voltage 额定负载nominal/rated load额定马力rated horsepower 额定容量rated capacity额定转速rated speed扼流圈/节流圈choke coil二次电压secondary voltage二极管diode二进制码binary code 二进制位，二进制数字binarydigit二维/2D 系统two dimensional system 二位控制器twostate/step controller 发射极，发射器emitter翻译程序，翻译器translator反磁性的diamagnetic, antimagnetic反馈控制feedback control 反偏置reverse biased反转触发器toggle flip-flop方法库way base(WB)方法库管理系统way base management system(WBMS)仿真，模拟simulation仿真/模拟simulation仿真[方]框图simulation block diagram 仿真程序simulation program仿真方法学simulation methodology仿真工作站simulation work station仿真过程simulation process仿真过程时间simulation process time仿真环境simulation environment仿真技术simulation technique仿真结果simulation result仿真类型simulation type仿真模型库simulation model library 仿真评价simulation evaluation仿真器，模拟器，模拟程序simulator仿真软件simulation software 仿真设备simulation equipment 仿真时钟simulation clock仿真实验模式库simulation experiment mode library仿真实验室simulation laboratory 仿真数据库simulation data base 仿真速度simulation velocity仿真算法库simulation algorithm library 仿真图形库simulation graphic library 仿真系统simulation system仿真信息库simulation information library仿真语言simulation language仿真运行simulation run仿真支持系统simulation support system仿真知识库simulation knowledge base 仿真中断simulation interrupt仿真中心simulation center仿真专家系统simulation expert system仿真作业simulation job非调速电气传动unadjustable speed electric drive非监督学习unsupervised learning 分布式控制distributed control分类，排序sort分类机，分类/排列程序sorter分离原理separation principle 分散控制decentralizedcontrol 分时time sharing分时控制time-sharing control分支，支路branch峰值peak value服务系统service system浮子液位计float levelmeter符号处理symbol processing 符号模型symbolic model符号语言symbolic language幅频特性magnitude/amplitude-frequency characteristics幅相特性magnitude-phase characteristics幅值裕量magnitude margin附件accessory感觉控制sensory control感应继电器induction relay隔膜阀diaphragm valve 根轨迹root locus跟踪控制tracking control 跟踪误差tracking error更新update工业机器人industrial robot工作电压operating voltage 工作站work station工作周期work cycle功耗power consumption/dissipation功率系数power factor 谷点电压valleyvoltage 故障电流fault current 惯性的inertial光触发晶闸管light-activated thyristor 光电管photocell光符阅读机（OCR）optical character reader光扫描器optical scanner过程控制process control过程自动化process automation 过渡过程transientprocess过渡过程时间settling time/transient time过载overload航天遥测space telemetry 耗散功率powerdissipation 黑箱black box厚度传感器thickness transducer 厚度计thicknessmeter/gauge 弧度radian缓冲存储器buffer storage换向器commutator 回路电流loop current 汇[点]sink汇编程序assembler惠特克-香农采样定理Whittaker-Shannon sampling theorem霍尔位移传感器Hall displacement transducer击穿电压breakdown voltage 机器语言machinelanguage 机械手manipulator极限环limit cycle集成电路integrated circuit集成电路芯片IC(integrated circuit) chip 计数器counter计算机辅助设计工作站work station for computer aided design 计算机辅助设计软件包software package of CAD计算机监控系统computer supervisory control system 计算机语言computer language记录record, register 记录仪recorder记录仪，记录器logger技术评价technical evaluation加法器adder加权法weighting method 加权函数weighting function加权矩阵weighting matrix加权因子weighting factor价值分析value analysis价值工程value engineering尖脉冲，窄脉冲spike pulse间隙clearance监督训练supervised training 监视器，监督程序monitor检流计，电流计galvanometer检验位，校验数字checkdigit简化模型simplified model键，关键码key交流电alternating current(AC)阶跃函数step function阶跃响应step response 节流阀，节流圈，扼流throttle节流孔，喷嘴orifice结构分解structural decomposition 结构可观测性/结构能观测性structural observability结构可控性/结构能控性structural controllability 结构可通性structural passability结构模型structure model结构摄动法structure perturbation approach结构稳定性structural stability结构协调structural coordination 截止频率cut-offfrequency解耦子系统decoupled subsystem解释interpret界面，接口interface经典控制理论classical control system晶片直径wafer diameter静差steady-state error 静态解耦static decoupling静态精[确]度static accuracy静态模型static model静态特性曲线staticcharacteristicscurve静态投入产出模型static input-output model矩形波逆变器square/rectangular wave inverter 句法分析syntactic analysis句法模式识别syntactic pattern recognition锯齿波sawtooth wave卡片穿孔机card punch卡片阅读机，读卡机card reader开关方式变换器switch-mode converter 开环系统open loopcontrol可编程控制PLC(ProgrammableLogicController)可变增益/放大系数variable gain可变增益法variable gain method 可测试性testability可分性separability可控硅silicon controlled rectifier(SCR)可理解性understandability可稳性stabilizability空载no-load/zero load控制工程control engineering 控制精度control accuracy控制盘control panel控制台console控制装置，控制器control unit快速恢复二极管fast recovery diode 宽度计width meter框图block diagram拉普拉斯变换Laplace transform冷却系统cooling system离散控制系统discrete control system 力臂moment arm 力传感器force transducer/gauge/sensor力矩器torquer励磁绕组excitation/exciting/field winding连续控制系统continuous control system量程span临界稳定性critical stability临界阻尼critical damping灵敏度分析sensitivity analysis 零点zero零和对策模型zero-sum game model 零基预算zero-based budget零输入响应zero-input response零状态响应zero-state response流程图flow chart/diagram/graph/sheet流量计flowmeter六分仪sextant漏电流leakage current 鲁棒控制robust control滤波电路filter circuit脉冲发生器pulse generator 脉动系数ripplefactor脉宽调制pulse-width modulation (PWM)慢变模态slow mode慢变状态slow state慢变子系统slow subsystem密度测量density measurement敏感元件sensing/sensitive element, sensor铭牌nameplate模板库template base模板匹配template matching 模糊控制fuzzy control 模拟计算机analog computer模型参考自适应控制系统model reference adaptive control system 目标仿真器target simulator目的系统teleological system逆 Z 变换inverse z-transform逆导型晶闸管reverse-conducting thyristor 耦合coupling批处理batch processing偏差信号deviation signal频分[制]遥测系统telemetering system of frequency division type 频域分析frequency domain analysis平稳随机过程stationary random/stochastic process 奇异控制singular control奇异摄动singular perturbation奇异吸引子singular attractor奇异线性系统singular linear system 起动starting,startup, start 气动的pneumatic气关式air-to-close（AC）气开式air-to-open（AO）前馈控制feed forward control 前置变换器pre-converter欠实时仿真slower-than-real-time simulation欠阻尼underdamping强耦合系统strongly coupled system强制换流force-commutated切换点switching point切换时间switching time清零，清除clear趋势法trend method趋势分析trend analysis权衡分析trade-off analysis扰动补偿disturbance compensation 扰动解耦disturbancedecoupling热传感器thermal/heat sensor热电偶，温差电偶thermocouple热交换器hot exchanger热交换器，换热器heat exchanger人工智能artificial intelligence(AI) 人机控制man-machinecontrol任务分配task allocation任务协调task coordination 任务优化taskoptimization 冗余redundancy冗余系统redundant system 软磁盘驱动器floppy diskdrive软件测试计划software testing plan 软件测试计划software testing plan 软件工具software tool软约束soft constraint润滑剂lubricant弱耦合系统weakly coupled system三端双向可控硅开关元件triac三极真空管triode三位控制器three state/step controller三重调制遥测系统triple modulation telemetering system 三轴转台three-axis table三轴转台three-axle table三轴姿态稳定three-axis attitude stabilization 上级问题upper level problem社会经济系统socioeconomic system社会控制论socio-cybernetics, social cybernetics射极跟随器emitter-follower神经网络neural network施塔克尔贝格决策理论Stackelberg decision theory 湿度测量humidity measurement时变参数time-varying parameter时变系统time-varying system时分[制]遥测系统telemetering system of time division type时间比例尺time scale factor时间常数time constant时间序列分析time series analysis 时间最优控制，快速控制time optimal control时序控制器time schedule controller时延time delay时域法time domain method时域分析time domain analysis时域模型降阶法time domain model reduction method 时滞系统time delay/time-lag system时钟，精密计时器timer时钟脉冲clock pulse实时控制real time control示教编程teaching programming 试运转test run受役系统slavedsystem输出output输入input鼠笼式squirrel-cage数据表data table/sheet/list 数据处理dataprocessing数字，数位，位digit数字的，数值的numeric,numerical 数字计算机digitalcomputer数字信号处理digitalsignalprocessing数组，阵列array双时标系统two-time scale system 双稳态电路bistablecircuit双向开关二极管diac顺序分解sequential decomposition顺序控制sequential control顺序控制器sequential controller顺序控制系统/顺控系统sequential control system 顺序优化sequential optimization瞬态偏差transient deviation死区dead band/area/belt/space伺服/随动控制servo control伺服/随动系统servo伺服电动机servomotor伺服阀servo valve伺服控制servo control 伺服马达/电机servomotor速度传感器velocity transducer速度传感器velocity transducer速度反馈velocity feedback速度误差系数velocity error coefficient 速开阀quick-opening valve随动系统，伺服机构servo随机存取random access随机控制系统stochastic control system 随机文法stochastic grammar随机下推自动机stochastic pushdown automaton随机有限自动机stochastic finite automaton索引index泰勒制Taylor system特征轨迹characteristiclocus 梯形图ladder diagram跳闸电路trip circuit通道，信道channel通断控制，开关式/继电器式/双位置控制on-off control同步电动机synchromotor铜端环copper end rings统计控制statistical control统计模型识别statistic pattern recognition统计预测statistical forecast/prediction 凸轮cam图灵机Turing machine图灵实验Turing test推力thrust推力器thruster推力矢量控制系统thrust vector control system拓扑结构topological structure外围设备peripheral equipment完全可观性，完全能观性complete observability完全可控性，完全能控性complete controllability微调fine adjustment维纳滤波Wiener filtering温彻斯特磁盘机，硬盘机Winchester disk drive温度变送器temperature transmitter温度测量仪表temperature measurement instrument温度传感器temperature sensor/transducer温度计thermometer温度开关temperature switch温度控制器temperature controller 稳定[性]极限stability limit稳定[性]判据/准则stability criterion稳定[性]条件stability condition 稳定系统stablesystem稳定性分析stability analysis稳定性理论stability theory稳定域stable region稳定裕度/裕量stability margin稳态steadystate稳态偏差steady state deviation稳态误差系数steady state error coefficient 稳态响应steadystateresponse稳态值steady state value稳压二极管Zener/voltage stabilizing diode 涡街流量计vortex shedding flowmeter涡轮流量计turbine flowmeter涡轮式发电机turbogenerator无偏估计unbiased estimation无源网络passive network物位变送器level transmitter误差信号error signal系统，[最]优化system optimization 系统辨识system identification 系统参数system parameter系统动力学模型system dynamics model系统方法system approach系统仿真system simulation系统分解system decomposition 系统工程systemengineering系统规划system planning系统环境system environment系统集结system aggregation系统建模system modeling系统矩阵system matrix系统可靠性system reliability系统可维护性system maintainability 系统灵敏度system sensitivity系统模型system model系统评价system assessment/evaluation系统示意图system diagram系统同构system isomorphism系统同态system homomorphism系统统计分析system statistical analysis 系统误差system error系统学syetematology系统诊断system diagnosis 系统状态system state显示装置display unit现场总线filed bus现代控制系统modern control system线电压line voltage线形时变控制系统linear time-varying control system 线性定常控制系统linear time-invariant control system 线性化模型linearized model线性控制系统理论linear control system theory相似性similarity相位控制，相控phase control向量雅普诺夫函数vector Liapunov function 肖特基二极管Schottky diodes效用函数utilityfunction 效用理论utilitytheory校验位checkdigit校准，标定calibrate协同学synergetics信号持续时间signalduration信号处理signalprocessing信号检测和估计signal detection and estimation 信号流，[程]图signalflowdiagram信号选择器signalselector信号重构signalreconstruction 信号转换器signalconverter信息，报文message序贯最小二乘估计sequential least squares estimation序列，顺序sequence旋进流量计swirlmeter, vortex precession flowmeter旋转变压器rotating transformer, revolver训练仿真器training simulator 压力表pressuregauge压力计manometer遥测telemetry, remote measurement/ metering/test遥测通信系统telemetering communication system 遥控remote control, telecontrol遥控力学/远动学telemechanics遥控系统remote control/telecontrol system液压控制hydraulic control一致渐近稳定性uniformly asymptotic stability 一致稳定性uniform stability仪表板/控制板dash panel移位，移数shift役使原理，从属原理slaving principle 溢出，上溢overflow印制电路printed circuit应变计，应变片strain gage应变式称重传感器strain gauge load cell用户友好界面user-friendly interface 游丝，细测量线hairspring有源网络active network语义网络semantic network 语音识别speech recognition 源[点] source远程通信telecommunication运算放大器op-amp(operational amplifier)杂散电感，漏电感stray inductance再生发电制动regenerative braking暂态特性曲线transient process characteristic curve闸流管thyratron闸流晶体管/可控硅thyristor黏性阻尼viscous damping占空比duty ratio力计tensiometer, tonometer真空管，电子管vacuum tube振动传感器vibration transducer 振动计vibrometer振弦式力传感器vibrating wire force transducer镇定，稳定stabilization镇定网络stabilizing network 正反馈positivefeedback正偏forward/positive biased 正偏压forward/positivebias正弦波sine/sinusoidal wave正向通道forward Path/channel直接数字控制，DDC direct digital control 指令instruction指令，命令command制表机tabulator治疗模型therapy model智能控制器intelligent control智能仪表intelligent instrument中间抽头变压器center-tapped transformer 终端控制terminal control终端设备，终端terminal unit轴axis轴承bearing逐步精化stepwise refinement 主观概率subjective probability 专家系统expert system转换文法transformation grammar转矩，扭矩torque转矩传感器torque transducer转速表tachometer转移图transition diagram 转子，电枢rotor转子流量计，浮子流量计rotameter装入，加载load状态变量state variable状态变量变换transformation of state variable状态反馈state feedback状态方程模型state equation model 状态估计state estimation状态观测器state observer状态轨迹state trajectory状态空间法state space method状态空间描述state space description状态图state diagram状态向量state vector状态约束state constraint状态转移矩阵state transition matrix状态转移模型state transition model子程序subroutine, subprogram 子系统subsystem字节，八位位组octet, byte字母数字的alphanumeric自持振荡sustained oscillation自动控制系统automatic control system 自耦变压器autotransformer自上而下测试top-down testing自上而下开发top-down development自校正控制self-tuning control纵向分解vertical decomposition阻抗impedance, resistance阻尼比damping ratio阻尼系数damping coefficient/factor 阻尼线圈damper/damping coil阻尼振荡damped/dying oscillation钻床drill, drilling machine, driller最短路径问题shortest path problem最佳优先搜索best-first search最小相位系统minimum phase system 最优控制系统optimal control system 作业程序task program作业级语言task level language 作业空间working space作业周期task cycle。

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越疆科技有限公司地址：深圳市南山区同富裕工业城三栋三楼网址：/目的本手册介绍了如何使用智能小车，使用户在使用时能挖掘更多功能，帮助用户快速上手。

读者对象本手册适用于：•客户工程师•销售工程师•安装调测工程师•技术支持工程师修订记录符号约定在本手册中可能出现下列标志，它们所代表的含义如下。

危险警告注意说明1. 注意事项 (1)1.1使用安全 (1)1.2售后条款 (1)1.2.1质保细则 (1)2. 产品简介 (3)2.1产品特性 (3)2.2零件清单 (3)2.3技术规格 (4)2.3.1技术参数 (4)3. 特性说明 (6)3.1AiStarter控制器 (6)3.1.1概述 (6)3.1.2A T Mega2560处理器 (6)3.1.3按键 (6)3.1.4LED (7)3.1.5USB (7)3.1.6接口说明 (8)3.2红外巡线传感器 (10)3.3超声波传感器 (10)3.4颜色传感器 (10)4. 安装指南 (11)4.1Mixly软件安装 (11)4.2Arduino IDE (11)5. 使用指南 (12)5.1Mixly使用说明 (12)5.2Arduino IDE使用说明 (12)5.3Blockly使用说明 (13)5.3.1设置小车运动方向和速度 (13)5.3.2设置小车运动方向\速度\时间 (14)5.3.3设置小车电机转速 (14)5.3.4启动小车超声波 (14)5.3.5探测障碍物 (15)5.3.6获取超声波探测距离 (15)5.3.7检测巡线路线 (15)5.3.8获取巡线传感器数据 (16)5.3.9获取地磁角度 (16)5.3.10设置颜色传感器白平衡 (17)5.3.11设置颜色传感器启停 (17)5.3.12获取RGB色值 (17)5.3.13检测颜色 (18)5.3.14获取按键状态 (18)5.3.15检测按键 (18)5.3.16获取光敏数值 (18)6. AI-Starter Demo (20)6.1自动巡线Demo (20)6.1.1介绍 (20)6.1.2操作步骤 (20)6.1.3关键代码说明 (20)6.2自动避障Demo (22)6.2.1介绍 (22)6.2.2操作步骤 (22)6.2.3关键代码说明 (22)6.3白平衡校准Demo (24)6.3.1介绍 (24)6.3.2操作步骤 (25)6.3.3关键代码说明 (25)6.4颜色识别与自动巡线Demo (25)6.4.1介绍 (25)6.4.2操作步骤 (25)6.4.3关键代码说明 (25)6.5机械臂协作Demo (26)6.5.1介绍 (26)6.5.2操作步骤 (27)6.5.3关键代码说明 (27)7. API接口 (30)7.1初始化 (30)7.2设置小车速度 (30)7.3设置小车运动方向/速度/时间 (30)7.4设置电机转速 (31)7.5设置电机参数 (31)7.6获取电机位置 (31)7.7初始化超声波传感器 (32)7.8获取超声波探测距离 (32)7.9探测障碍物 (32)7.10获取巡线数据 (33)7.11获取地磁角度 (33)7.12地磁校准 (33)7.13设置颜色白平衡 (34)7.14启停颜色传感器 (34)7.15检测颜色 (34)7.16获取RGB色值 (35)7.17初始化按键 (35)7.18获取按键状态 (36)7.19设置灯光状态 (36)7.20获取光敏数值 (36)7.21设置超声波传感器检测距离 (37)1.注意事项1.1 使用安全•安装电池时请根据电池盒里的正负极提示进行安装，以防电池装反。

（完整版）S7-300PLC中自主设计双极性温控PID算法

（完整版）S7-300PLC中⾃主设计双极性温控PID算法S7-300 PLC中⾃主设计程序控温PID算法Self-Design of Programming Temperature Control PIDAlgorithm in S7-300 PLC南阳理⼯学院殷华⽂[摘要]本设计采⽤位置型算法思想，⽤梯形图语⾔在西门⼦S7-300 PLC中⾃主编写程序控温PID算法程序，实现对夹套锅炉的升温—保温—降温双极性控制。

算法中加⼊控制带、偏差死区、输出死区、输出限幅、积分清零等多种控制⼿段。

在温度曲线拐点处，为了避免控制的延迟及超调，采⽤提前控制、变控制参数的⽅法。

监控结果显⽰，本PID程序对夹套锅炉⽔温控制超调量较⼩，稳态误差⼩于0.2℃。

[关键词]⾃主设计、位置式PID算法、程序控温Abstract：The design of PID programming module independently to control electric heating boiler and cooling bipolar based on Siemens S7-300 PLC. The bipolar PID algorithm has used position type algorithm, and a structured programming. it can operate PID algorithm only when it ranges the deviation in the control , so as to avoid integral saturation phenomenon. it has applied dead-time processing to the deviation. Then in order to avoid the control delay and the overshoot, it has used advanced control and variable parameter control method during the cooling process.The control algorithm has introduced some control means,such as,the output dead, the output limiting, the integral reset and so on. Monitoring results show that the PID program modules have targeted control to the temperature object , smaller overshoot and the steady-state error is less than 0.2 DEG c.Key words：self-design,position type PID algorithm,programming temperature control1引⾔在⾃动化领域，⼤多数PLC、DCS控制器中都有PID算法程序，但是由于算法思想和源程序不公开，给⽤户正确使⽤带来困难。

51单片机PID的算法实现程序

51单片机PID的算法实现程序用整型变量来实现PID算法，由于是用整型数来做的,所以也不是很精确,但是对于很多的使用场合,这个精度也够了，关于系数和采样电压全部是放大10倍处理的.所以精度不是很高. 但是也不是那么低,大部分的场合都够了. 实在觉得精度不够, 可以再放大10倍或者100倍处理,但是要注意不超出整个数据类型的范围就可以了.本程序包括PID计算和输出两部分.当偏差>10度全速加热,偏差在10度以内为PID计算输出. 具体的参考代码参见下面：*///================================================================// pid.H// Operation about PID algorithm procedure// C51编译器Keil 7.08//================================================================// 作者:zhoufeng// Date :2007-08-06// All rights reserved.//================================================================#include <reg52.h>#include <intrins.h>typedef unsigned char uint8;typedef unsigned int uint16;typedef unsigned long int uint32;/**********函数声明************/void PIDOutput ();void PIDOperation ();/*****************************/typedef struct PIDValue{uint32 Ek_Uint32[3]; //差值保存，给定和反馈的差值uint8 EkFlag_Uint8[3]; //符号，1则对应的为负数，0为对应的为正数uint8 KP_Uint8;uint8 KI_Uint8;uint8 KD_Uint8;uint16 Uk_Uint16; //上一时刻的控制电压uint16 RK_Uint16; //设定值uint16 CK_Uint16; //实际值}PIDValueStr;PIDValueStr PID;uint8 out ; // 加热输出uint8 count; // 输出时间单位计数器/*********************************PID = Uk + KP*[E(k)-E(k-1)]+KI*E(k)+KD*[E(k)-2E(k-1)+E(k-2)];(增量型PID算式)函数入口: RK(设定值),CK(实际值),KP,KI,KD函数出口: U(K)//PID运算函数********************************/void PIDOperation (void){uint32 Temp[3]; //中间临时变量uint32 PostSum; //正数和uint32 NegSum; //负数和Temp[0] = 0;Temp[1] = 0;Temp[2] = 0;PostSum = 0;NegSum = 0;if( PID.RK_Uint16 > PID.RK_Uint16 ) //设定值大于实际值否？{if( PID.RK_Uint16 - PID.RK_Uint16 >10 ) //偏差大于10否？{_Uint16 = 100; } //偏差大于10为上限幅值输出(全速加热) else{Temp[0] = PID.RK_Uint16 - PID.CK_Uint16; //偏差<=10,计算E(k)PID.EkFlag_Uint8[1]=0; //E(k)为正数//数值移位PID.Ek_Uint32[2] = PID.Ek_Uint32[1];PID.Ek_Uint32[1] = PID.Ek_Uint32[0];PID.Ek_Uint32[0] = Temp[0];/****************************************/if( PID.Ek_Uint32[0] >PID.Ek_Uint32[1] ) //E(k)>E(k-1)否？{Temp[0]=PID.Ek_Uint32[0] - PID.Ek_Uint32[1]; //E(k)>E(k-1)PID.EkFlag_Uint8[0]=0; } //E(k)-E(k-1)为正数else{Temp[0]=PID.Ek_Uint32[0] - PID.Ek_Uint32[1]; //E(k)<E(k-1)PID.EkFlag_Uint8[0]=1; } //E(k)-E(k-1)为负数/****************************************/Temp[2]=PID.Ek_Uint32[1]*2 ; // 2E(k-1)if( (PID.Ek_Uint32[0]+ PID.Ek_Uint32[2])>Temp[2] ) //E(k-2)+E(k)>2E(k-1)否？{Temp[2]=(PID.Ek_Uint32[0]+PID.Ek_Uint32[2])-Temp[2];//E(k-2)+E(k)>2E(k-1)PID.EkFlag_Uint8[2]=0; } //E(k-2)+E(k)-2E(k-1)为正数else{Temp[2]=Temp[2]-(PID.Ek_Uint32[0]+ PID.Ek_Uint32[2]); //E(k-2)+E(k)<2E(k-1)PID.EkFlag_Uint8[2]=1; } //E(k-2)+E(k)-2E(k-1)为负数/****************************************/Temp[0] = (uint32)PID.KP_Uint8 * Temp[0]; // KP*[E(k)-E(k-1)]Temp[1] = (uint32)PID.KI_Uint8 * PID.Ek_Uint32[0]; // KI*E(k)Temp[2] = (uint32)PID.KD_Uint8 * Temp[2]; // KD*[E(k-2)+E(k)-2E(k-1)]/*以下部分代码是讲所有的正数项叠加，负数项叠加*//**********KP*[E(k)-E(k-1)]**********/if(PID.EkFlag_Uint8[0]==0)PostSum += Temp[0]; //正数和elseNegSum += Temp[0]; //负数和/********* KI*E(k)****************/if(PID.EkFlag_Uint8[1]==0)PostSum += Temp[1]; //正数和else; //空操作，E(K)>0/****KD*[E(k-2)+E(k)-2E(k-1)]****/if(PID.EkFlag_Uint8[2]==0)PostSum += Temp[2]; //正数和elseNegSum += Temp[2]; //负数和/***************U(K)***************/PostSum += (uint32)_Uint16;if(PostSum > NegSum ) // 是否控制量为正数{ Temp[0] = PostSum - NegSum;if( Temp[0] < 100 ) //小于上限幅值则为计算值输出_Uint16 = (uint16)Temp[0];else_Uint16 = 100; //否则为上限幅值输出}else //控制量输出为负数，则输出0(下限幅值输出)_Uint16 = 0;}}else{ _Uint16 = 0; }}*********************************函数入口: U(K)函数出口: out(加热输出)//PID运算植输出函数********************************/void PIDOutput (void){static int i;i=_Uint16;if(i==0)out=1;else out=0;if((count++)==5)//如定时中断为40MS,40MS*5=0.2S(输出时间单位),加热周期20S(100等份) { //每20S PID运算一次count=0;i--;}}。

16A系列温度过程控制器说明书

CALL TO ORDER: U.S. Phone 219 879-8000 • U.K. Phone (+44) (0)1494-461707 • Australia Phone (+61) (0) 2 4272 2055259Latest microprocessor based technology affords full programmability with complete array of f eatures in compact ultra low cost unit. 16A Series Temperature/Process Controller features universal input, Self-Tune PID, Fuzzy Logic, and dual f our-digit LED displays f or process and set point value.Selectable inputs can be thermocouple, RTD, current or voltage. Available outputs are solid-state relay, relay, pulsed voltage, or proportional current.Programmable alarm (optional) can be reset automatically or manually. Front panel is waterproof and corrosion resistant (UL type 4X), making it ideal for sanitary applications. Replace electronics without wiring changes (via removable front panel). Self diagnostics, nonvolatile memory and selectable control modes are all designed for greater productivity. Four security levels are password protected. On-off, P, PI or PID manual tune control functions can be selected or the controller will Self-Tune automatically for best PID control.The 16A2 of f ers the best value in Standard Features in a Process and Temperature control. In addition to the features listed above, the 16A2 offers Peak/Valley indication, Percent Output indication, Digital Input Filter, and a host of others.Temperature/Process Controller1/16 DIN, Universal lnput, Fuzzy Logic, Self-TunePIDSeries 16A** These options may not be combined with each other.SPECIFICATIONSSelectable Inputs:Thermocouple, RTD, DC voltage, or DC current (see input ranges).Display:Two four-digit LED displays, 0.3 in (7.62 mm) high.Display Resolution: 1 degree or 0.1 degree (sensor dependent), or 1count.Accuracy:±0.25% of span ±1 least significant digit.Supply Voltage: 100 to 240 VAC nominal, +10% -15%, 50 to 400 Hz single phase; 132 to 240 VDC +10% -20%.Operating Temperature: 14 to 131°F (-10 to 55°C).Power Consumption: 5 VA maximum.Control Output Ratings:SSR: 2.0 A at 240 VAC resistive at 77°F (25°C). De-rates to 1.0 A at 130°F (55°C). Minimum load of 100 mA; DC SSR: 1.75 A at 32 VDC maximum;Relay: SPST , 3A at 240 VAC resistive, 1.5 A @ 240 VAC inductive; Pilot duty rating: 250 VA, 2 A @ 120 VAC, 1 A @ 240 VAC; Alarm relay: SPST , 3 A @ 240 VAC resistive; 1.5 A @ 240 VACinductive. Pilot duty rating: 240 VA, 2 A @ 120 VAC or 1 A @ 240 VAC; Switched voltage: 15 VDC at 20 mA;Proportional current: 0 to 20 mADC, scalable, into 600 ohms maximum.Weight: 8 oz (227 g).Agency Approvals: UL E83725, CE.Front Panel Rating: NEMA 4X (IP66).Serial Communications (Optional): RS-232 or RS-485 with either LoveLink ™Software or Modbus ®RTU protocol.Modbus ® is a registered trademark of Schnieder Automation, Inc.OPTIONS (Add as a suffix to model number)-934**, Process Signal Output, PV or SV.Isolated 0 to 20 mADC . . . . . . . . . . . . . . . . . . . . . . . . . . . . .add $67.50-936**, Process Signal Output, PV or SV.Isolated 0 to 10 VDC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .add 67.50-992**,RS-485 Serial Communications Lovelink TM Protocol . .add 82.00-993**,RS-232 Serial Communications Lovelink TM Protocol . .add 82.00-995**, RS-232 Serial Communications Modbus RTV Protocol add 99.50-996**, RS-485 Serial Communications Modbus RTV Protocol add 99.50-9502, 12-24 VDC/VAC power input . . . . . . . . . . . . . . . . . . . . .add 48.00ACCESSORIESMN-1,Mini-Node ™USB/RS-485 converter . . . . . . . . . . . . . . . . . .$75.00LoveLinks III,Configuration software . . . . . . . . . . . . . . . . . . . . .35.00b A-600,R/C snubber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16.25b Items are subject to Schedule B discounts.。

多合一控制器PLC编程软件的使用技巧与优化

多合一控制器PLC编程软件的使用技巧与优化PLC（Programmable Logic Controller）是近年来在工业自动化领域应用广泛的控制设备。

随着技术的发展和应用场景的不断扩大，PLC也不再是简单的单一功能设备，而是发展成了多合一控制器。

多合一控制器PLC编程软件的使用技巧与优化对于提高工程效率和精确控制至关重要。

本文将介绍多合一控制器PLC编程软件的使用技巧与优化方案。

一、多合一控制器PLC编程软件概述多合一控制器PLC编程软件是一种用于编写、调试和管理PLC程序的工具软件。

它通过图形化界面提供了方便快捷的编程环境，并可以与其他工具软件进行集成，实现更加丰富的功能和优化。

二、多合一控制器PLC编程软件的基本功能多合一控制器PLC编程软件具备以下基本功能：1. 程序编写：提供图形化编程界面，支持多种编程语言，如梯形图、函数图和指令列表等，方便用户根据需求进行程序编写。

2. 调试与验证：软件支持在线模拟和离线调试，可以对编写的程序进行全面的验证和调试，排除错误并保证程序的可靠性。

3. 数据监控与分析：通过软件可以实时监控和记录PLC控制器的运行数据，提供图表显示和数据分析功能，帮助用户分析PLC运行状况和效率。

4. 远程访问与控制：支持通过网络远程访问和控制PLC，并提供安全认证和权限管理等功能，方便用户随时随地监控和管理设备。

三、多合一控制器PLC编程软件的使用技巧1. 熟练掌握编程语言：根据不同的应用需求和个人习惯，选择合适的编程语言进行开发。

熟练掌握编程语言的语法和规则，可以提高编程效率和程序的可读性。

2. 模块化设计：合理划分程序模块，将程序分解为多个子程序，提高代码的可维护性和可重用性。

同时，模块化设计也方便不同开发人员之间的协作和交流。

3. 使用注释和命名规范：编写程序时，应养成良好的注释和命名规范习惯。

合理的注释可以提高代码的可读性和可维护性，规范的命名方便其他人理解并修改程序。

PID控制LQRH控制器实例(已修正错误)

目录0 引言 (1)1 原系统的特性 (2)1.1 参考论文系统结构图分析 (2)1.2 控制对象的传递函数 (3)2 PID控制器设计 (4)2.1 PID控制器原理 (4)2．2 PID控制器设计 (6)2.3 控制器性能分析 (7)2.4 Simulink仿真link仿真 (8)3 极点配置控制器的设计 (10)3.1 极点配置设计 (10)3.2 极点配置控制器分析 (11)3.3 Simulink仿真 (12)4 LQR控制器的设计 (13)4.1 LQR控制器原理 (13)4.2 LQR控制器设计 (13)4.4 Simulink下仿真 (16)5 H∞控制器的设计 (19)5.1 H∞控制器原理 (19)5.2 H∞控制器设计 (21)5.3 H∞控制器分析 (27)5.4 Simulink下仿真 (27)6 综合比较 (28)参考文献 (29)0 引言随着磁盘驱动器轨道密度的不断增长，越来越多的算法被引入到磁盘驱动器的磁头定位上；由于H∞控制能详细的指定闭环系统的结构，利用H∞控制来增强HDD伺服系统的性能和鲁棒性成为一种可行的方法；本文将对几种常见的控制器：PID,极点配置，LQR和H∞控制器进行研究，并比较各种控制的优缺点。

本文则分别介绍了4种不同的控制控制器来改善系统的动态性能、稳态性能、跟踪性能和抗干扰性能。

1 原系统的特性1.1 参考论文系统结构图分析本文通过阅读《A Comparative Study of the Use of the Generalized Hold Function for HDDs》一文，对硬盘伺服系统的模型进行分析，如图1-1所示是参考论文系统结构图。

图1-1 参考论文系统结构图其中P 为控制对象、K 为控制器、S 为采样器、y 采样器测量值、v 为采样测量噪声、ω为外部干扰、W 为低通滤波器、U 为控制器输出、α、β和η比例因子。

参考论文采用的是H ∞控制器来改善一个离散系统性能，本文在没有考虑采样器情况下，针对控制对象P 来设计几种控制器来改善一个连续系统性能，并做了一个横向比较。