pid簡(jiǎn)介及英語(yǔ)翻譯.

1、PID ControlIntroductionThe PID controller is the most common form of feedback. It was an essential element of early governors and it became the standard tool when process control emerged in the 1940s. In process control today, more than 95% of the control loops are of PID type, most loops are actual

2、ly PI control. PID controllers are today found in all areas where control is used. The controllers come in many different forms. There are standalone systems in boxes for one or a few loops, which are manufactured by the hundred thousands yearly. PID control is an important ingredient of a distribut

3、ed control system. The controllers are also embedded in many special purpose control systems. PID control is often combined with logic, sequential functions, selectors, and simple function blocks to build the complicated automation systems used for energy production, transportation, and manufacturin

4、g. Many sophisticated control strategies, such as model predictive control, are also organized hierarchically. PID control is used at the lowest level; the multivariable controller gives the set points to the controllers at the lower level. The PID controller can thus be said to be the “bread and bu

5、tter of control engineering. It is an important component in every control engineers tool box.PID controllers have survived many changes in technology, from mechanics and pneumatics to microprocessors via electronic tubes, transistors, integrated circuits. The microprocessor has had a dramatic influ

6、ence the PID controller. Practically all PID controllers made today are based on microprocessors. This has given opportunities to provide additional features like automatic tuning, gain scheduling, and continuous adaptation.The AlgorithmWe will start by summarizing the key features of the PID contro

7、ller. The “textbook” version of the PID algorithm is described by: 6.1where y is the measured process variable, r the reference variable, u is the control signal and e is the control error（e = y）. The reference variable is often called the set point. The control signal is thus a sum of three terms:

8、the P-term （which is proportional to the error）, the I-term （which is proportional to the integral of the error）, and the D-term （which is proportional to the derivative of the error）. The controller parameters are proportional gain K, integral time Ti, and derivative time Td. The integral, proporti

9、onal and derivative part can be interpreted as control actions based on the past, the present and the future as is illustrated in Figure 2.2. The derivative part can also be interpreted as prediction by linear extrapolation as is illustrated in Figure 2.2. The action of the different terms can be il

10、lustrated by the following figures which show the response to step changes in the reference value in a typical case.Effects of Proportional, Integral and Derivative ActionProportional control is illustrated in Figure 6.1. The controller is given by D6.1E with Ti = and Td=0. The figure shows that the

11、re is always a steady state error in proportional control. The error will decrease with increasing gain, but the tendency towards oscillation will also increase.Figure 6.2 illustrates the effects of adding integral. It follows from D6.1E that the strength of integral action increases with decreasing

12、 integral time Ti. The figure shows that the steady state error disappears when integral action is used. Compare with the discussion of the “magic of integral action” in Section 2.2. The tendency for oscillation also increases with decreasing Ti. The properties of derivative action are illustrated i

13、n Figure 6.3.Figure 6.3 illustrates the effects of adding derivative action. The parameters K and Ti are chosen so that the closed loop system is oscillatory. Damping increases with increasing derivative time, but decreases again when derivative time becomes too large. Recall that derivative action

14、can be interpreted as providing prediction by linear extrapolation over the time Td. Using this interpretation it is easy to understand that derivative action does not help if the prediction time Td is too large. In Figure 6.3 the period of oscillation is about 6 s for the system without derivative

15、Chapter 6. PID ControlFigure 6.1Figure 6.2Derivative actions cease to be effective when Td is larger than a 1 s (one sixth of the period). Also notice that the period of oscillation increases when derivative time is increased.There is much more to PID than is revealed by （6.1）. A faithful implementa

16、tion of the equation will actually not result in a good controller. To obtain a good PID controller it is also necessary to consider。Figure 6.3Different ParameterizationsThe PID algorithm given by Equation（6.1）can be represented by the transfer function 6.7 6.8 6.9 An interacting controller of the f

17、orm Equation D6.8E that corresponds to a non-interacting controller can be found only ifThe parameters are then given by 6.10The non-interacting controller given by Equation （6.7） is more general, and we will use that in the future. It is, however, sometimes claimed that the interacting controller i

18、s easier to tune manually.It is important to keep in mind that different controllers may have different structures when working with PID controllers. If a controller is replaced by another type of controller, the controller parameters may have to be changed. The interacting and the non-interacting f

19、orms differ only when both I and the D parts of the controller are used. If we only use the controller as a P, PI, or PD controller, the two forms are equivalent. Yet another representation of the PID algorithm is given by 6.11The parameters are related to the parameters of standard form through The

20、 representation Equation （6.11） is equivalent to the standard form, but the parameter values are quite different. This may cause great difficulties for anyone who is not aware of the differences, particularly if parameter 1/ki is called integral time and kd derivative time. It is even more confusing

21、 if ki is called integration time. The form given by Equation （6.11） is often useful in analytical calculations because the parameters appear linearly. The representation also has the advantage that it is possible to obtain pure proportional, integral, or derivative action by finite values of the pa

22、rameters.PID介紹PID控制器是反饋控制的最常見(jiàn)形式。因?yàn)樵缭?0年代它就成為了過(guò)程控制的標(biāo)準(zhǔn)工具。在今天的過(guò)程控制業(yè)中，超過(guò)95%的控制回路是PID類型，多數(shù)實(shí)際上是PI 控制。PID控制是分布控制系統(tǒng)的一種重要組成部分?？刂破鞅浑[藏在許多其他控制系統(tǒng)下面。PID 控制與邏輯控制經(jīng)常結(jié)合在一起,連續(xù)作用、選擇器，和簡(jiǎn)單的功能模塊一起構(gòu)成復(fù)雜自動(dòng)化系統(tǒng)，可以應(yīng)用在發(fā)電、運(yùn)輸，以及制造業(yè)。許多經(jīng)典的控制策略，譬如模型有預(yù)測(cè)性的控制。PID控制是使用在要求水平較低的場(chǎng)合；PID控制器應(yīng)用在底層。PID控制器在每個(gè)控制工程師的應(yīng)用實(shí)例里都能經(jīng)常見(jiàn)到。近年來(lái)PID控制器在技術(shù)生產(chǎn)上也產(chǎn)生了許

23、多變化，從機(jī)械到微處理器控制由電子管，晶體管,組合電路組成的控制系統(tǒng)。微處理器對(duì)PID控制器有著強(qiáng)烈的影響。實(shí)際上今天制作的所有PID控制器都是建立在微處理器的基礎(chǔ)上的。這就有機(jī)會(huì)擴(kuò)展其他的特點(diǎn)：像自動(dòng)定調(diào)，獲取預(yù)定，和連續(xù)的適應(yīng)。6.2 算法我們開(kāi)始講解PID控制器的主要特點(diǎn)。 PID算法的描述： 6.1這里 y 是被測(cè)量的處理可變量, r 參考可變量, u 是控制信號(hào)，e是控制誤差 。參考變量經(jīng)?？梢员环Q為是固定的點(diǎn)?？刂菩盘?hào)包含三個(gè)量，P-term，I-term，D-term，控制器的參數(shù)包括比例系數(shù)K，整體時(shí)間Ti，和Td。以過(guò)去，現(xiàn)在和未來(lái)為基礎(chǔ)的控制軌跡可解釋整體，比例項(xiàng)和輸出部份的關(guān)系。圖中舉例。在不同時(shí)間的運(yùn)動(dòng)可以表示輸出部分的一個(gè)典型的例子。在參數(shù)值方面作一下改變，即可預(yù)測(cè)下一時(shí)間的走向問(wèn)題。PID的作用圖6.1說(shuō)明的是典型的比例控制。控制器給定Ti=，Td=0。表示在比例控制中總存在有一種穩(wěn)定狀態(tài)誤差。獲取值增加誤差將減少，但系統(tǒng)穩(wěn)定性將受到影響。圖 6.2 說(shuō)明增加積分式的作用。它跟隨圖6.1而來(lái)增加時(shí)間Ti.當(dāng)積分式運(yùn)行使用。穩(wěn)定狀態(tài)誤差將逐漸的