PID中英文對照翻譯

1、中英文互譯PID Contro lIntroductionsystems。 PID controlfunction blocks toThe PID controller is the most commonform 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 l

2、oops are of PID type, most loops are 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 cont

3、rol is an important ingredient of a distributed control system 。 The controllers are also embedded in many special purpose controlis often combined with logic , sequential functions , selectors, and simplebuild the complicated automation systems used for energy productiontransportation, andmanufactu

4、ringMany sophisticated control strategiessuch as modelpredictive controlare also organized hierarchicallyPID control is used at the lowest level ；the multivariable controller gives the set points to the controllers at the lower levelThePID controller can thus be saidto be the bread and butter of con

5、trol engineering. It is animportant component in every control engineer s tool boxPID controllers have survived many changes in technology , from mechanics and pneumatics tomicroprocessors via electronic tubes , transistors, integrated circuits. The microprocessor hashad a dramatic influence the PID

6、 controller 。 Practically all PID controllersmade today are basedon microprocessors 。 This has given opportunitiesto provide additional features like automatictuning, gain scheduling, and continuous adaptation.6。2 The AlgorithmWewill start by summarizingthe key featuresof the PID controller 。 The te

7、xtbook versionof the PID algorithm is described byT：0e dde tT 一6.1where y is the measured process variable ,the reference variable , u is the control signaland e is the control error(e = ysp - y) . The reference variable is often called the set pointThe 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 isproportional to the derivative of the error).The controller parameters are proportional gainK, integral timeTi, and derivative timeTd。 The integral , proportional

9、 and derivative partcan be interpreted as control actions based on the past,the present and the future as isillustrated in Figure 2.2Figure 6 。 1The derivative part can also be interpreted as prediction by linearextrapolation as is illustrated in Figure 2.2. The action of the different terms can be

10、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 withT= 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 integralaction increases with decreasing

12、 integral time T i。 The figure showsthat the steadystate 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 T. The properties of derivative action are illustrated in F

13、igure 6。 3.Figure 6。 3 illustrates the effects of adding derivative action.The parameters K and Ti arechosen 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 c

14、an 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 C

15、hapter 6。 PID Control(IIH2020inFigure 6 。 2Derivative actions cease to be effective whenTd is larger than a 1 s (one sixth of theperiod). Also notice that the period of oscillation increases when derivative time is increased.A PerspectiveThere is muchmore toPID than is revealedby (6.1 )。A faithfulim

16、plementationof the equationwill actually not resultin a good controller。 To obtaina good PIDcontroller it isalso necessaryto consider 。Figure 6.3Noise filtering and high frequency roll offSet point weighting and 2 DOFWindupTuningComputer implementationIn the case of the PID controller these issues e

17、merged 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 book 。6.3 Filtering and Set Point WeightingDiff

18、erentiation is always sensitive to noise 。This is clearly seen from the transfer functionG s） = s of a differentiator which goes to infinity for larges。The following example is alsoilluminatingy t sint nwhere the noise is sinusoidal noise with frequency wsint sin tan n。 The derivative of the signal

19、is如 cost nt dtcost ancosntThe signal to noise ratio for the original signal is 1/an but the signal to noise ratio ofthe differentiated signal is w/an. This ratio can be arbitrarily high if w is largeIn a practical controller with derivative actionit is there for necessary to limit the highfrequency

20、gain of the derivative term. This can be done by implementing the derivative term as6.2sKTd1 sTd Ninstead of D=sTY。The approximation given by （6。2） can be interpreted as the ideal derivative sTi filtered by a first order system with the time constantTJ N The approximation acts as aderivative for low

21、 frequency signal components 。 The gain, however , is limited to KN This means that high-frequency measurement noise is amplified at most by a factorKN Typical valuesof N are 8 to 20。Further limitation of the high-frequency gainThe transfer function from measurement y to controller output u of a PID

22、 controller with the approximate derivative is1STis KT d1 sTd NThis controller has constant gainlim C s K 1 Nsat high frequencies 。 It follows from the discussion on robustness against process variationsin Section 5 。 5 that it is highly desirableto roll offthe controller gainat high frequenciesThis

23、 can be achieved by additionallow pass filtering of the control signal by1 sTfwhere Tf is the filter time constant andn is the order of the filter. The choice ofTf isa compromise between filtering capacity and performance。 The value of T f can be coupled to thecontroller time constants in the same w

24、ay as for the derivative filterabove。 If the derivativetime is used, T尸 Td/Nis a suitable choice 。 If the controller is only PI, Tf =Ti / Nmay be suitable 。The controller can also be implemented as11C s K 1 STh 26 o 3sTiT 1 STd NThis structure has the advantage that we can develop the design methods

25、 for an ideal PID controller and use an iterative design procedure 。 The controller is first designed for the process P (s)。The design gives the controller parameter Td- An ideal controller for the process P (s)/2 (1+sT/N) is then designed giving a new value ofTd etc。 Such a procedure will also give

26、 aclear picture of the tradeoff between performance and filteringWhenusing the control law given by (6.1)Set Point Weightingit follows that a step change in the reference signalwill result in an impulse in the control signal。 This is often highly undesirable there forderivative action is frequently

27、not appliedto the reference signal.This problem can be avoidedby filtering the reference value before feeding it to the controller。 Another possibility isto let proportional action act only on part of the reference signal。 This is called set pointweighting 。 A PID controller given by(6。1) then becom

28、es1tu t K br t y t eTi0,dr t dy td Td c-1d dt dtwhere b and c are additional parameter。 The integral term must be based on error feedbackto ensure the desired steady state 。Thecontroller given by D6。4E has a structure with two degreesof freedom because the signal path fromy to u is different from th

29、at fromr to u。 The transferfunction from r to u is, , .1cr S K b t cSTdsT i6.5Time tFigure 6。4 Response to a step in the reference for systems with different set point weightsb= 0 dashed, b = 0 5 full and b=1 0 dash dotted 。 The process has the transfer functionP(s)=1/(s+1) 3 and the controller para

30、meters arek = 3, ki = 15 and kd = 15。and the transfer function fromy to u iscy s1K 1 sTdsTiThe system obtained with the controllerSet point weighting is thus a special case of controllers having two degrees of freedom.(6.4) respond to load disturbances and measurementnoise in the same way as the con

31、troller (6.1) 。 The response to reference values can be modifiedby the parameters b and c。This is illustrated in Figure 6。 4, which shows the response of aPID controller to set point changes , load disturbances, and measurement errors for different values of b。 The figure shows clearly the effect of

32、 changingb。 The overshoot for set-pointchanges is smallest for b = 0, which is the case where the reference is only introduced in the integral term , and increases with increasing b。The parameter c is normally zero to avoid large transients in the control signal due to sudden changes in the set poin

33、t.6。4 Different ParameterizationsThe PID algorithm given by Equation(6 。 1) can be represented by the transfer function-，1G s K 1sTd6.7sTiK kT68T iTdT dTdAn interacting controller of the form Equation D6。8E that corresponds to a non interacting controller can be found only ifTi 4TdThe parameters are

34、 then given byK K 萬1 ,1 4Td TI11 4Td T6o 10T d +11 4Td TThe 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 is easier to tune manually.It is important to keep in mind that diff

35、erent controllers mayhave different structures when working with PID controllers. If a controller is replaced by another type of controller, the。If we only use the controller as。 Yet another representation of theskdcontroller parameters mayhave to be changed o The interacting and the non-interacting

36、 forms differ only when both I and the D parts of the controller are used a P , PI , or PD controller , the two forms are equivalent PID algorithm is given byo 11G s kThe parameters are related to the parameters of standard form throughk Kki：kdKTdI iThe representation Equation （6。11） is equivalent t

37、o the standard form, but the parametervalues 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 andkd derivative time 。 Itis even more confusing if ki is called integration time 。 The form giv

38、en by Equation （6。11） is often useful in analytical calculations because the parameters appear linearly 。Therepresentation also has the advantage that it is possible to obtain pure proportional , integral , or derivative action by finite values of the parameters.PID控制6.1介紹PID控制器是反饋控制的最常見形式。因?yàn)樵缭?0年代它

39、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%勺控制回路是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.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(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.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(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PID控

40、制器有著強(qiáng)烈的影響.實(shí)際上今天制作的所有 PID控制器都是建獲取預(yù)定，和連續(xù)的適應(yīng)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),6。2算法我們開始講解PID控制器的主要特點(diǎn)PID算法的描述：de tTd/1 tu t K e t e dTi0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 ysp y .參考變量經(jīng)?？梢员环Q為是固定的點(diǎn).控制信號包含三個(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。以過去，現(xiàn)在和未來為基礎(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

41、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)測下一時(shí)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=s, 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 o 2說明增加積分式的彳用。它跟隨圖 6。1而來增加時(shí)間Ti。當(dāng)積分式運(yùn)行使用.穩(wěn)定狀態(tài)誤差 將逐漸的消失。相比較，說明在圖6.3減少Ti,波動(dòng)繼續(xù)增大。圖6 o 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(dòng)的。當(dāng)輸出時(shí) 間過長時(shí)，導(dǎo)出時(shí)間將被阻值再一次增加 ，減少也是一樣。當(dāng)在時(shí)間Td作線形補(bǔ)償取消輸出可以得到預(yù)測的結(jié)果。用簡

42、單的方法解釋，如果預(yù)測時(shí)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6So圖 6.2。當(dāng)Td比1S（六分之一的周期時(shí)間）大的時(shí)候，輸出的作用停止是有效的.也要注意當(dāng)輸出時(shí)間增加的時(shí)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(shí)際上一個(gè)好控制器，必需得有一個(gè)好的PID控制器而獲得一個(gè)好的PID控制器，也需要認(rèn)真地考慮一下。05101520匕=0.7 Tj- = 4-fi = Ori05101520圖 6.3 o噪聲過濾和高頻率關(guān)閉凝固點(diǎn)衡量和2 DOF終結(jié)調(diào)諧計(jì)算機(jī)執(zhí)行在使用PID控制器的時(shí)候，有些問題就會(huì)涌現(xiàn)出來，但他們實(shí)際上最重要的是在所

43、有控制中的實(shí)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(diǎn)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 sint n t這里的噪聲是正弦信號，頻率為 W O信號的導(dǎo)數(shù)是dy t +cost n t dtsint ansintcost ancosntW是足夠大的這個(gè)比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D sKTd621 sTd N替換D=sT,Y。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(gè)以時(shí)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 o這就意味著，高頻率測量 噪聲大多由因素KN被放大