pid控制外文翻譯

1、<p>　　PID controller</p><p>　　A proportional–integral–derivative controller (PID controller) is a generic .control loop feedback mechanism widely used in industrial control systems. A PID controller att

2、empts to correct the error between a measured process variable and a desired setpoint by calculating and then outputting a corrective action that can adjust the process accordingly.</p><p>　　The PID controll

3、er calculation (algorithm) involves three separate parameters; the Proportional, the Integral and Derivative values. The Proportional value determines the reaction to the current error, the Integral determines the reacti

4、on based on the sum of recent errors and the Derivative determines the reaction to the rate at which the error has been changing. The weightedsum of these three actions is used to adjust the process via a control element

5、 such as the position of a control valve or </p><p>　　Some applications may require using only one or two modes to provide the appropriate system control. This is achieved by setting the gain of undesired co

6、ntrol outputs to zero. A PID controller will be called a PI, PD, P or I controller in the absence of the respective control actions. PI controllers are particularly common, since derivative action is very sensitive to me

7、asurement noise, and the absence of an integral value may prevent the system from reaching its target value due to the control </p><p>　　Note: Due to the diversity of the field of control theory and applicat

8、ion, many naming conventions for the relevant variables are in common use.</p><p>　　1.Control loop basics</p><p>　　A familiar example of a control loop is the action taken to keep one's show

9、er water at the ideal temperature, which typically involves the mixing of two process streams, cold and hot water. The person feels the water to estimate its temperature. Based on this measurement they perform a control

10、action: use the cold water tap to adjust the process. The person would repeat this input-output control loop, adjusting the hot water flow until the process temperature stabilized at the desired value.</p><p&g

11、t;　　Feeling the water temperature is taking a measurement of the process value or process variable (PV). The desired temperature is called the setpoint (SP). The output from the controller and input to the process (the t

12、ap position) is called the manipulated variable (MV). The difference between the measurement and the setpoint is the error (e), too hot or too cold and by how much.As a controller, one decides roughly how much to change

13、the tap position (MV) after one determines the temperature (PV),</p><p>　　If a controller starts from a stable state at zero error (PV = SP), then further changes by the controller will be in response to cha

14、nges in other measured or unmeasured inputs to the process that impact on the process, and hence on the PV. Variables that impact on the process other than the MV are known as disturbances and generally controllers are u

15、sed to reject disturbances and/or implement setpoint changes. Changes in feed water temperature constitute a disturbance to the shower process.</p><p>　　In theory, a controller can be used to control any pro

16、cess which has a measurable output (PV), a known ideal value for that output (SP) and an input to the process (MV) that will affect the relevant PV. Controllers are used in industry to regulate temperature, pressure, flo

17、w rate, chemical composition, speed and practically every other variable for which a measurement exists. Automobile cruise control is an example of a process which utilizes automated control.</p><p>　　Due to

18、 their long history, simplicity, well grounded theory and simple setup and maintenance requirements, PID controllers are the controllers of choice for many of these applications.</p><p>　　2.PID controller th

19、eory</p><p>　　Note: This section describes the ideal parallel or non-interacting form of the PID controller. For other forms please see the Section "Alternative notation and PID forms".</p>

20、<p>　　The PID control scheme is named after its three correcting terms, whose sum constitutes the manipulated variable (MV). Hence:</p><p>　　where Pout, Iout, and Dout are the contributions to the outpu

21、t from the PID controller from each of the three terms, as defined below.</p><p>　　2.1. Proportional term</p><p>　　The proportional term makes a change to the output that is proportional to the

22、current error value. The proportional response can be adjusted by multiplying the error by a constant Kp, called the proportional gain.</p><p>　　The proportional term is given by:</p><p><b&g

23、t;　　Where</b></p><p>　　Pout: Proportional output </p><p>　　Kp: Proportional Gain, a tuning parameter </p><p>　　e: Error = SP ? PV </p><p>　　t: Time or instantaneo

24、us time (the present) </p><p>　　Change of response for varying KpA high proportional gain results in a large change in the output for a given change in the error. If the proportional gain is too high, the sy

25、stem can become unstable (See the section on Loop Tuning). In contrast, a small gain results in a small output response to a large input error, and a less responsive (or sensitive) controller. If the proportional gain is

26、 too low, the control action may be too small when responding to system disturbances.</p><p>　　In the absence of disturbances, pure proportional control will not settle at its target value, but will retain a

27、 steady state error that is a function of the proportional gain and the process gain. Despite the steady-state offset, both tuning theory and industrial practice indicate that it is the proportional term that should cont

28、ribute the bulk of the output change.</p><p>　　2.2.Integral term</p><p>　　The contribution from the integral term is proportional to both the magnitude of the error and the duration of the error

29、. Summing the instantaneous error over time (integrating the error) gives the accumulated offset that should have been corrected previously. The accumulated error is then multiplied by the integral gain and added to the

30、controller output. The magnitude of the contribution of the integral term to the overall control action is determined by the integral gain, Ki.</p><p>　　The integral term is given by:</p><p>　　I

31、out: Integral output </p><p>　　Ki: Integral Gain, a tuning parameter </p><p>　　e: Error = SP ? PV </p><p>　　τ: Time in the past contributing to the integral response </p><

32、;p>　　The integral term (when added to the proportional term) accelerates the movement of the process towards setpoint and eliminates the residual steady-state error that occurs with a proportional only controller. How

33、ever, since the integral term is responding to accumulated errors from the past, it can cause the present value to overshoot the setpoint value (cross over the setpoint and then create a deviation in the other direction)

34、. For further notes regarding integral gain tuning and controller st</p><p>　　2.3 Derivative term</p><p>　　The rate of change of the process error is calculated by determining the slope of the e

35、rror over time (i.e. its first derivative with respect to time) and multiplying this rate of change by the derivative gain Kd. The magnitude of the contribution of the derivative term to the overall control action is ter

36、med the derivative gain, Kd.</p><p>　　The derivative term is given by:</p><p>　　Dout: Derivative output </p><p>　　Kd: Derivative Gain, a tuning parameter </p><p>　　e: E

37、rror = SP ? PV </p><p>　　t: Time or instantaneous time (the present) </p><p>　　The derivative term slows the rate of change of the controller output and this effect is most noticeable close to t

38、he controller setpoint. Hence, derivative control is used to reduce the magnitude of the overshoot produced by the integral component and improve the combined controller-process stability. However, differentiation of a s

39、ignal amplifies noise and thus this term in the controller is highly sensitive to noise in the error term, and can cause a process to become unstable if the noise an</p><p>　　2.4 Summary</p><p>

40、　　The output from the three terms, the proportional, the integral and the derivative terms are summed to calculate the output of the PID controller. Defining u(t) as the controller output, the final form of the PID algor

41、ithm is:</p><p>　　and the tuning parameters are</p><p>　　Kp: Proportional Gain - Larger Kp typically means faster response since the </p><p>　　larger the error, the larger the Propo

42、rtional term compensation. An excessively large proportional gain will lead to process instability and oscillation. </p><p>　　Ki: Integral Gain - Larger Ki implies steady state errors are eliminated quicker.

43、 The trade-off is larger overshoot: any negative error integrated during transient response must be integrated away by positive error before we reach steady state. </p><p>　　Kd: Derivative Gain - Larger Kd d

44、ecreases overshoot, but slows down transient response and may lead to instability due to signal noise amplification in the differentiation of the error. </p><p>　　3. Loop tuning</p><p>　　If the

45、PID controller parameters (the gains of the proportional, integral and derivative terms) are chosen incorrectly, the controlled process input can be unstable, i.e. its output diverges, with or without oscillation, and is

46、 limited only by saturation or mechanical breakage. Tuning a control loop is the adjustment of its control parameters (gain/proportional band, integral gain/reset, derivative gain/rate) to the optimum values for the desi

47、red control response.</p><p>　　The optimum behavior on a process change or setpoint change varies depending on the application. Some processes must not allow an overshoot of the process variable beyond the s

48、etpoint if, for example, this would be unsafe. Other processes must minimize the energy expended in reaching a new setpoint. Generally, stability of response (the reverse of instability) is required and the process must

49、not oscillate for any combination of process conditions and setpoints. Some processes have a degree of n</p><p>　　There are several methods for tuning a PID loop. The most effective methods generally involve

50、 the development of some form of process model, then choosing P, I, and D based on the dynamic model parameters. Manual tuning methods can be relatively inefficient.</p><p>　　The choice of method will depend

51、 largely on whether or not the loop can be taken "offline" for tuning, and the response time of the system. If the system can be taken offline, the best tuning method often involves subjecting the system to a s

52、tep change in input, measuring the output as a function of time, and using this response to determine the control parameters.</p><p>　　Choosing a Tuning Method</p><p>　　MethodAdvantagesDisadvant

53、ages</p><p>　　Manual TuningNo math required. Online method.Requires experienced </p><p>　　personnel.</p><p>　　Ziegler–NicholsProven Method. Online method.Process upset, some </p&

54、gt;<p>　　trial-and-error, very aggressive tuning.</p><p>　　Software ToolsConsistent tuning. Online or offline method. May include </p><p>　　valve and sensor analysis. Allow simulation bef

55、ore downloading.Some cost </p><p>　　and training involved.</p><p>　　Cohen-CoonGood process models.Some math. Offline method. Only good for </p><p>　　first-order processes.</p>

56、<p>　　3.1 Manual tuning</p><p>　　If the system must remain online, one tuning method is to first set the I and D values to zero. Increase the P until the output of the loop oscillates, then the P shou

57、ld be left set to be approximately half of that value for a "quarter amplitude decay" type response. Then increase D until any offset is correct in sufficient time for the process. However, too much D will caus

58、e instability. Finally, increase I, if required, until the loop is acceptably quick to reach its reference after a load dis</p><p>　　3.2Ziegler–Nichols method</p><p>　　Another tuning method is f

59、ormally known as the Ziegler–Nichols method, introduced by John G. Ziegler and Nathaniel B. Nichols. As in the method above, the I and D gains are first set to zero. The "P" gain is increased until it reaches t

60、he "critical gain" Kc at which the output of the loop starts to oscillate. Kc and the oscillation period Pc are used to set the gains as shown:</p><p>　　3.3 PID tuning software</p><p>

61、　　Most modern industrial facilities no longer tune loops using the manual calculation methods shown above. Instead, PID tuning and loop optimization software are used to ensure consistent results. These software packages

62、 will gather the data, develop process models, and suggest optimal tuning. Some software packages can even develop tuning by gathering data from reference changes.</p><p>　　Mathematical PID loop tuning induc

63、es an impulse in the system, and then uses the controlled system's frequency response to design the PID loop values. In loops with response times of several minutes, mathematical loop tuning is recommended, because t

64、rial and error can literally take days just to find a stable set of loop values. Optimal values are harder to find. Some digital loop controllers offer a self-tuning feature in which very small setpoint changes are sent

65、to the process, allowing the c</p><p>　　Other formulas are available to tune the loop according to different performance criteria.</p><p>　　4 Modifications to the PID algorithm</p><p&

66、gt;　　The basic PID algorithm presents some challenges in control applications that have been addressed by minor modifications to the PID form.One common problem resulting from the ideal PID implementations is integral &l

67、t;/p><p>　　windup. This can be addressed by:</p><p>　　Initializing the controller integral to a desired value </p><p>　　Disabling the integral function until the PV has entered the con

68、trollable region </p><p>　　Limiting the time period over which the integral error is calculated </p><p>　　Preventing the integral term from accumulating above or below pre-determined bounds <

69、/p><p>　　Many PID loops control a mechanical device (for example, a valve). Mechanical maintenance can be a major cost and wear leads to control degradation in the form of either stiction or a deadband in the m

70、echanical response to an input signal. The rate of mechanical wear is mainly a function of how often a device is activated to make a change. Where wear is a significant concern, the PID loop may have an output deadband t

71、o reduce the frequency of activation of the output (valve). This is accomplishe</p><p>　　5. Limitations of PID control</p><p>　　While PID controllers are applicable to many control problems, the

72、y can perform poorly in some applications.PID controllers, when used alone, can give poor performance when the PID loop gains must be reduced so that the control system does not overshoot, oscillate or "hunt" a

73、bout the control setpoint value. The control system performance can be improved by combining the feedback (or closed-loop) control of a PID controller with feed-forward (or open-loop) control. Knowledge about the system

74、(suc</p><p>　　For example, in most motion control systems, in order to accelerate a mechanical load under control, more force or torque is required from the prime mover, motor, or actuator. If a velocity loo

75、p PID controller is being used to control the speed of the load and command the force or torque being applied by the prime mover, then it is beneficial to take the instantaneous acceleration desired for the load, scale t

76、hat value appropriately and add it to the output of the PID velocity loop controller. T</p><p>　　feedback value. Working together, the combined open-loop feed-forward controller and closed-loop PID controlle

77、r can provide a more responsive, stable and reliable control system.</p><p>　　Another problem faced with PID controllers is that they are linear. Thus, performance of PID controllers in non-linear systems (s

78、uch as HVAC systems) is variable. Often PID controllers are enhanced through methods such as PID gain scheduling or fuzzy logic. Further practical application issues can arise from instrumentation connected to the contro

79、ller. A high enough sampling rate, measurement precision, and measurement accuracy are required to achieve adequate control performance.</p><p>　　A problem with the Derivative term is that small amounts of m

80、easurement or process noise can cause large amounts of change in the output. It is often helpful to filter the measurements with a low-pass filter in order to remove higher-frequency noise components. However, low-pass f

81、iltering and derivative control can cancel each other out, so reducing noise by instrumentation means is a much better choice. Alternatively, the differential band can be turned off in many systems with little loss of c&

82、lt;/p><p>　　6. Cascade control</p><p>　　One distinctive advantage of PID controllers is that two PID controllers can be used together to yield better dynamic performance. This is called cascaded PI

83、D control. In cascade control there are two PIDs arranged with one PID controlling the set point of another. A PID controller acts as outer loop controller, which controls the primary physical parameter, such as fluid le

84、vel or velocity. The other controller acts as inner loop controller, which reads the output of outer loop controller as set</p><p>　　7. Physical implementation of PID control</p><p>　　In the ear

85、ly history of automatic process control the PID controller was implemented as a mechanical device. These mechanical controllers used a lever, spring and a mass and were often energized by compressed air. These pneumatic

86、controllers were once the industry standard.Electronic analog controllers can be made from a solid-state or tube amplifier, a capacitor and a resistance. Electronic analog PID control loops were often found within more c

87、omplex electronic systems, for example, the head p</p><p>　　Most modern PID controllers in industry are implemented in software in programmable logic controllers (PLCs) or as a panel-mounted digital controll

88、er. Software implementations have the advantages that they are relatively cheap and are flexible with respect to the implementation of the PID algorithm.</p><p><b>　　PID控制器</b></p><p&g

89、t;　　比例積分微分控制器（PID調(diào)節(jié)器）是一個控制環(huán)，廣泛地應(yīng)用于工業(yè)控制系統(tǒng)里的反饋機(jī)制。PID控制器通過調(diào)節(jié)給定值與測量值之間的偏差，給出正確的調(diào)整，從而有規(guī)律地糾正控制過程。</p><p>　　PID控制器算法涉及到三個部分：比例，積分，微分。比例控制是對當(dāng)前偏差的反應(yīng)，積分控制是基于新近錯誤總數(shù)的反應(yīng)，而微分控制則是基于錯誤變化率的反應(yīng)。這三種控制的結(jié)合可用來調(diào)節(jié)過程系統(tǒng)，例如調(diào)節(jié)閥的位置，或者加熱系

90、統(tǒng)的電源調(diào)節(jié)。根據(jù)具體的工藝要求，通過PID控制器的參數(shù)整定，從而提供調(diào)節(jié)作用?？刂破鞯捻憫?yīng)可以被認(rèn)為是對系統(tǒng)偏差的響應(yīng)。注意一點(diǎn)的是，PID算法不一定就是系統(tǒng)或系統(tǒng)穩(wěn)定性的最佳控制。</p><p>　　一些應(yīng)用可能只需要運(yùn)用一到兩種方法來提供適當(dāng)?shù)南到y(tǒng)控制。這是通過把不想要的控制輸出置零取得。在控制系統(tǒng)中存在P,PI,PD,PID調(diào)節(jié)器。PI調(diào)節(jié)器很普遍，因?yàn)槲⒎挚刂茖y量噪音非常敏感。積分作用的缺乏可以防止

91、系統(tǒng)根據(jù)控制目標(biāo)而達(dá)到它的目標(biāo)值。</p><p>　　注釋：由于控制理論和應(yīng)用領(lǐng)域的差異，很多相關(guān)變量的命名約定是常用的。</p><p><b>　　控制環(huán)基礎(chǔ) </b></p><p>　　一個關(guān)于控制環(huán)類似的例子就是保持水在理想溫度，涉及到兩個過程，冷、熱水的混合。人可以憑觸覺估測水的溫度?；诖怂麄冊O(shè)計(jì)一個控制行為：用冷水龍頭調(diào)整過程

92、。重復(fù)這個過程，調(diào)節(jié)熱水流直到溫度處于期望的穩(wěn)定值。</p><p>　　感覺水溫就是對過程值或變量的測量。期望得到的溫度稱為給定值。控制器的輸出對象和過程的輸入對象稱為控制參數(shù)。測量值與給定值之間的差就是偏差值，太高、太低或正常。作為一個控制器，在確定溫度給定值后，就可以粗略決定改變閥門位置多少，以及怎樣改變偏差值。首次估計(jì)即是PID控制器的比例度的確定。當(dāng)它幾乎正確時，PID控制器的積分作用就是起著逐漸調(diào)整

93、溫度的作用。微分作用就是根據(jù)水溫變得更熱、更冷，以及變化速率來決定什么時候、怎樣調(diào)整那些閥門。當(dāng)偏差小時而做了一個大變動，相當(dāng)于一個大的調(diào)整控制器，會導(dǎo)致超調(diào)。如果控制器反復(fù)進(jìn)行大的變動并且反復(fù)越過給定值的改變，控制環(huán)將會不穩(wěn)定。輸出值將在期望值或一常量周圍擺動，甚至破壞系統(tǒng)穩(wěn)定性。人不會這樣做，因?yàn)槲覀兪怯兄腔鄣目刂迫藛T，可以從歷史經(jīng)驗(yàn)中學(xué)習(xí)，但PID控制器沒有學(xué)習(xí)能力，必須正確的設(shè)定。為有效的控制系統(tǒng)選擇正確的參數(shù)被稱為整定控制器。

94、</p><p>　　如果控制器在零偏差從穩(wěn)定開始，然后進(jìn)一步的變化將導(dǎo)致其它一些影響過程的能測量、不能測量值的變化，并且作用于偏差值上。除主過程以外，其他的對擾動有影響的過程可以用來抑制擾動或?qū)崿F(xiàn)對目標(biāo)值的改變。供給水溫的變化就構(gòu)成了對過程的一個擾動。</p><p>　　理論上，控制器能用來控制可測量對象，以及可以影響偏差的輸出、輸入標(biāo)準(zhǔn)值的所有過程參數(shù)。控制器在工業(yè)中被用來調(diào)節(jié)溫度，

95、壓力，流速，化學(xué)組成，速度以及其它任何存在可測量的對象。汽車游覽控制就是一個自動化的過程控制的例子。</p><p>　　由于它們悠久的歷史，簡易，良好的理論基礎(chǔ)以及簡單的設(shè)置、維護(hù)要求，PID控制器被許多應(yīng)用實(shí)踐所采納。</p><p>　　2.PID控制器理論</p><p>　　注釋：這部分描述PID控制器理想平行或非相互作用的形式。關(guān)于其他形式，請看“其它的

96、表達(dá)式和PID形式”這部分。</p><p>　　PID控制是根據(jù)它的三個參數(shù)而命名的，三參數(shù)結(jié)合起來就形成控制參數(shù)。因此：</p><p>　　Pout，Iout和Dout是控制器的三個參數(shù)，下面分別予以確定。</p><p><b>　　2.1比例度</b></p><p>　　比例度是根據(jù)當(dāng)前的錯誤值而做出的變動。

97、比例度可以通過恒定的Kp增加來調(diào)整，稱為比例增益。</p><p><b>　　比例度計(jì)算如下：</b></p><p><b>　　Pout:比例度</b></p><p>　　Kp：比例系數(shù)，協(xié)調(diào)參數(shù)。</p><p>　　e:偏差=SP-PV</p><p>　　t:時

98、間或瞬時時間（當(dāng)前的）</p><p>　　一個高的比例增益產(chǎn)生于一種輸出值的大的變化。如果比例增益太高，系統(tǒng)將變得不穩(wěn)定。響應(yīng)地，一個小的調(diào)整產(chǎn)生于一小的輸出變化，而如果比例增益太低，當(dāng)對系統(tǒng)振蕩作出反映時，控制作用可能太小。</p><p>　　缺少擾動的情況下，純粹的比例控制不能完全解決問題，但是將保留從過程中獲得的具有比例增益的功能的穩(wěn)態(tài)偏差。盡管有穩(wěn)態(tài)補(bǔ)償，理論和工業(yè)實(shí)踐都表明比

99、例度在輸出控制中起到大部分的作用。</p><p><b>　　2.2積分值</b></p><p>　　積分值的大小與偏差的大小及持續(xù)時間成正比。根據(jù)即時的超時的錯誤改正，進(jìn)行積累補(bǔ)償。積累的誤差通過積分調(diào)節(jié)后再作用于輸出。對總的控制作用的積分大小由積分時間常數(shù)來決定，即Ki，積分值計(jì)算如下：</p><p><b>　　Iout：

100、積分值</b></p><p>　　Ki:積分時間常數(shù)，協(xié)調(diào)參數(shù)</p><p>　　e:偏差=SP-PV</p><p><b>　　ζ：積分時間</b></p><p>　　積分值加速面向設(shè)定值的過程運(yùn)動并且消除殘余的只與控制器發(fā)生作用的穩(wěn)態(tài)偏差。然而，因?yàn)榉e分從過去的積累誤差作出反應(yīng)，引起當(dāng)前的值越過設(shè)