控制中英文對照翻譯

1、外文資料與翻譯PID Contro lIntroductionThe 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 ar

2、e actually 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 d

3、istributed control system. The controllers are also embeddedin 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 manuf

4、acturing. 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 saidto be the “ bread

5、 and butter of control engineering. It is an important component in every control engineer ' s 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

6、dramatic influence 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.6.2 The AlgorithmWe will start by summarizing the key features

7、 of the PID controller. The “textbook “ version of the PID algorithm is described by:6.11tdetu t K e t e d dTi0出where y is the measured process variable, the reference variable,u is the control signal and e is the control error (e = ysp - y) . The reference variable is often calledthe set point. The

8、 control signal is thus a sum of three terms: the P-term(which isproportional 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 gainK, integral time Ti,

9、and derivative time Td. The integral, proportional 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.

10、2. The action of the different terms can be illustrated 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

11、 with Ti =and Td=0. The figure shows that there is always a steady state error inproportional control. The error will decrease with increasing gain, but the tendency towards osc川ation will also increase.Figure 6.2 illustrates the effects of adding integral. It follows from D6.1E that the strength of

12、 integral action increases with decreasing integral time TThe figure shows that the steady state error disappears when integral action is used. Compare with the discussion of the “magicof integral action "in Section 2.2. The tendency for oscillation also increaseswith decreasing T. The properti

13、es of derivative action are illustrated in Figure 6.3.Figure 6.3 川ustrates 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 decreasesagain when derivative time becomes too

14、 large. Recall that derivative action 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

15、6 s for the system without derivative Chapter 6. PID ControlFigure 6.1Figure 6.2Derivative actions cease to be effective wherTd is larger than a 1 s (one sixth of the period). Also notice that the period of oscillation increases when derivative time is increased.A PerspectiveThere is much more to PI

16、D than is revealed by (6.1). A faithful implementation of the equation will actually not result in a good controller. To obtain a good PID controller it is also necessary to considerFigure 6.3Noise filtering and high frequency roll offSet point weighting and 2 DOFWindupTuningComputer implementationI

17、n the case of the PID controller these issues emerged organically as the technology developed but they are actually important in the implementation of all controllers. Many of these questions are closely related to fundamental properties of feedback, some of them have been discussed earlier in the b

18、ook.6.3 Filtering and Set Point WeightingDifferentiation is always sensitive to noise. This is clearly seen from the transfer function G(s) =s of a differentiator which goes to infinity for large s. The followingexample is also 川uminating.y t sint n tsint sinanntwhere the noise is sinusoidal noise w

19、ith frequency w. The derivative of the signalis虹 cost nt dtcost ancos ntThe signal to noise ratio for the original signal is 1/an but the signal to noise ratio of the differentiated signal is w/an. This ratio can be arbitrarily high if w is large.In a practical controller with derivative action it i

20、s there for necessary to limit the high frequency gain of the derivative term. This can be done by implementing the derivative term asd -sKTd.1 sTd Ninstead of D=sTdY. The approximation given by (6.2) can be interpreted as the ideal derivative sTd filtered by a first-order system with the time const

21、ant Td/N. The approximation acts as a derivative for low-frequency signal components. The gain, however, is limited to KN. This means that high-frequency measurementnoise is amplified at most by a factor KN. Typical values ofN are 8 to 20.Further limitation of the high-frequency gain_s KT d_1 sTd NT

22、he transfer function from measurement y to controller output u of a PID controller with the approximate derivative is1C S K 1 sTiThis controller has constant gainlim C s Ksat high frequencies. It follows from the discussion on robustness against process variations in Section 5.5 that it is highly de

23、sirable to roll off the controller gain at high frequencies. This can be achieved by additionallow pass filtering of the control signal byF s 1n1 sTfwhere Tf is the filter time constant andn is the order of the filter. The choice of Tf is a compromise between filtering capacity and performance. The

24、value of T f can be coupled to the controller time constants in the same way as for the derivative filter above. If the derivative time is used, T f= Td/N is a suitable choice. If the controller is only PI, T f =Ti/N may be suitable.The controller can also be implemented as-11C s K 1 sTd 26.3sTi11 s

25、Td NThis structure has the advantage that we can develop the design methods for an ideal PID controller and use an iterative design procedure. The controller is first designed for the processP(s). The design gives the controller parameter Td. An ideal2controller for the process P(s)/(1+sT/N) is then

26、 designed giving a new value of Tdetc. Such a procedure will also give a clear picture of the tradeoff between performance and filtering.Set Point WeightingWhen using the control law given by (6.1) it follows that a step change in the reference signal will result in an impulse in the control signal.

27、 This is often highly undesirable there for derivative action is frequently not applied to the reference signal. This problem can be avoided by filtering the reference value before feeding it to the controller. Another possibility is to let proportional action act only on part of the reference signa

28、l. This is called set point weighting. A PID controller given by (6.1) then becomesut K br t y te dTi0dr t dy tTd c-dT -dT6.4where b and c are additional parameter. The integral term must be based on error feedback to ensure the desired steady state. The controller given by D6.4E has a structure wit

29、h two degrees of freedom because the signal path fromy to u is different from that from r to u. The transfer function from r to u is6.5U s ,1R7Gs K b 王 csTdFigure 6.4 Response to a step in the reference for systems with different set point weights b= 0 dashed,b = 0 5 full and b=1 0 dash dotted. The

30、process has the transfer function P (s) =1/ (s+1) 3 and the controller parameters ark = 3, k = 1 5 and kd = 1 5.and the transfer function fromy to u isrTCysTd6.6Set point weighting is thus a special case of controllers having two degrees of freedom.The system obtained with the controller (6.4) respo

31、nd to load disturbances and measurement noise in the same way as the controller (6.1) . The response to reference values can be modified by the parameters b and c. This is illustrated in Figure 6.4, which shows the response of a PID controller to set-point changes, load disturbances, and measurement

32、 errors for different values of b. The figure shows clearly the effect of changing b. The overshoot for set-point changes is smallest forb =0, which is the case where the reference is only introduced in the integral term, and increases with increasingb.The parameter c is normally zero to avoid large

33、 transients in the control signal due to sudden changes in the set-point.6.4 Different ParameterizationsThe PID algorithm given by Equation (6.1) can be represented by the transfer function一. ，1crG s K 1 sTd6.7sTiK KT T i6.8Ti T i T d6.9TT i T dAn interacting controller of the form Equation D6.8E th

34、at corresponds to a non-interacting controller can be found only ifT i 4T dThe parameters are then given byKKM14Td Ti6.10Ti 9114TdTd Ti114TdThe 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 interacti

35、ng controller is 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 no

36、n-interacting forms 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 byG s k skd6.11sThe parameters are related to the parameters of s

37、tandard form throughKk KkikdKTdI iThe 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 1k is called integral time and kd derivat

38、ive time. It is even more confusing 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 derivativ

39、e action by finite values of the parameters.第6章PID控制6.1 介紹PID控制器是反饋控制的最常見形式。因為早在 40年代它就成為了過程控 制的標(biāo)準(zhǔn)工具。在今天的過程控制業(yè)中,超過95%的控制回路是PID類型，多數(shù) 實際上是PI控制。PID控制是分布控制系統(tǒng)的一種重要組成部分。控制器被隱 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，和簡單的功能模塊一起構(gòu)成復(fù)雜自動化系統(tǒng)，可以應(yīng)用在發(fā)電，運輸，以及制造業(yè)。許多經(jīng)典的控制策略，譬如模型有預(yù)測性的控制。PID控制是使用 在要求水平較低的場合；PID控制器應(yīng)用在底層

40、。PID控制器在每個控制工程師 的應(yīng)用實例里都能經(jīng)常見到。近年來PID控制器在技術(shù)生產(chǎn)上也產(chǎn)生了許多變化，從機械到微處理器控 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PID控制器有著強烈的影響。實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。 這就有機會擴展其他的特點：像自動定調(diào)，獲取預(yù)定，和連續(xù)的適應(yīng)。6.2 算法我們開始講解PID控制器的主要特點。PID算法的描述：,，1t , de tu t K e t e d d6.1Ti0 1dt這里y是被測量的處理可變量,r參考可變量，u是控制信號，e是控制誤差e y p y o參考變量經(jīng)常可以被稱為是固定的點?？刂菩?/p>

41、號包含三個量，P-term, I-term, D-term,控制器的參數(shù)包括比例系數(shù) K,整體時間Ti,和Td。以 過去，現(xiàn)在和未來為基礎(chǔ)的控制軌跡可解釋整體， 比例項和輸出部份的關(guān)系。圖 中舉例。在不同時間的運動可以表示輸出部分的一個典型的例子。 在參數(shù)值方面 作一下改變，即可預(yù)測下一時間的走向問題。PID的作用圖6.1說明的是典型的比例控制.控制器給定Ti=oo, 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說明增加積分式的作用。它跟隨圖 6.1而來增加時間Ti.當(dāng)積分式運行使用。穩(wěn)定狀態(tài)誤差將逐漸的消失。相比較，說明在圖

42、6.3減少Ti ,波動 繼續(xù)增大.圖6.3舉例說明增加輸出的方法的效果。 參數(shù)K和Ti被選定以便閉環(huán) 系統(tǒng)是振動的。當(dāng)輸出時間過長時，導(dǎo)出時間將被阻值再一次增加，減少也是一 樣。當(dāng)在時間Td作線形補償取消輸出可以得到預(yù)測的結(jié)果。 用簡單的方法解釋, 如果預(yù)測時間Td太大，導(dǎo)出將沒有影響。在圖 6.3中，振蕩的周期是沒有引出 的，大約是6S。510152005101520圖6.1圖 6.2.當(dāng)Td比1S （六分之一的周期時間）大的時候，輸出的作用停止是有效的。 也要注意當(dāng)輸出時間增加的時候，振蕩的周期也將增加。圖6.1說明有許多比PID更好的系統(tǒng)，但是，實際上一個好控制器，必需 得有一個好的PI

43、D控制器。而獲得一個好的PID控制器，也需要認(rèn)真地考慮一 下。噪聲過濾和高頻率關(guān)閉凝固點衡量和2 DOF終結(jié)調(diào)諧計算機執(zhí)行在使用PID控制器的時候，有些問題就會涌現(xiàn)出來，但他們實際上最重要 的是在所有控制中的實施。許多問題與反饋本身是緊密地聯(lián)系在一起的。其中， 有些在早期的一些資料中就已經(jīng)被研究過。6.3過濾和凝固點的衡量微分對噪聲總是敏感的。像G(s) = s的微分器。以下的例子可以有力的說明例子6.1-DIFFERENTIATION 放大高頻率噪音，參考信號y t sintsint sinanntw 。信號的導(dǎo)數(shù)是cost cosan這里的噪聲是正弦信號，頻率為dy t costdt針對噪音的信號比率為原始的信號是 1倍，但噪音的信號比率是被區(qū)分的 如果w是足夠大的這個比率是可能任意提高的。從一種積分作用控制器來看，是有必要限制積分范圍的，以得到高頻率。這 可以由做積分的范圍決定6.2sKTd1 sTd N替換口=$丁丫。由(6.2)的f得到的近似值，可以解釋為理想的積分 sTd過 濾了由一個以時間常數(shù)Td/N的優(yōu)先處理的系統(tǒng)。近似值以一種低頻率信號組分。 但是，這種獲取，限制了 KN。這就意味著，高頻率測量噪聲大多由因素 KN被放 大，N的典型的價值是8到20。制信高頻率獲取的進(jìn)一步測量y對控制裝置輸出u這種控制器有穩(wěn)定的輸入的一種PID控制器與近似積