pid控制器畢業(yè)設(shè)計外文翻譯

1、<p><b>　　附 錄</b></p><p><b>　　一、英文原文</b></p><p>　　PID controller</p><p>　　A proportional–integral–derivative controller (PID controller) is a generic co

2、ntrol loop feedback mechanism(controller) widely used in industrial control systems –a PID is the most commonly used feedback controller. A PID controller calculates an "error" value as the difference between a

3、 measuredprocess variable and a desired setp oint. The controller attempts to minimize the error by adjusting the process control inputs. In the absence of knowledge of the underlying process, PID controllers are</p&g

4、t;<p>　　The PID controller calculation (algorithm) involves three separate parameters, and is accordingly sometimes calledthree-term control: the proportional, the integral and derivative values, denoted P, I, and

5、 D. The proportionalvalue determines the reaction to the current error, the integral value determines the reaction based on the sum of recent errors, and the derivative value determines the reaction based on the rate at

6、which the error has been changing. The weighted sum of these three actions </p><p>　　By tuning the three constants in the PID controller algorithm, the controller can provide control action designed for spec

7、ific process requirements. The response of the controller can be described in terms of the responsiveness of the controller to an error, the degree to which the controller overshoots the setpoint and the degree of system

8、 oscillation. Note that the use of the PID algorithm for control does not guarantee optimal control of the system or system stability.</p><p>　　Some applications may require using only one or two modes to pr

9、ovide the appropriate system control. This is achieved by setting the gain of undesired control outputs to zero. A PID controller will be called a PI, PD, P or I controller in the absence of the respective control action

10、s. PI controllers are fairly common, since derivative action is sensitive to measurement noise, whereas the absence of an integral value may prevent the system from reaching its target value due to the control action.<

11、;/p><p>　　Note: Due to the diversity of the field of control theory and application, many naming conventions for the relevant variables are in common use.</p><p>　　Control loop basics</p>&l

12、t;p>　　A familiar example of a control loop is the action taken when adjusting hot and cold faucet valves to maintain the faucet water at the desired temperature. This typically involves the mixing of two process strea

13、ms, the hot and cold water. The person touches the water to sense or measure its temperature. Based on this feedback they perform a control action to adjust the hot and cold water valves until the process temperature sta

14、bilizes at the desired value.</p><p>　　Sensing water temperature is analogous to taking a measurement of the process value or process variable (PV). The desired temperature is called the setpoint (SP). The i

15、nput to the process (the water valve position) is called the manipulated variable (MV). The difference between the temperature measurement and the setpoint is the error (e), that quantifies whether the water is too hot o

16、r too cold and by how much.</p><p>　　After measuring the temperature (PV), and then calculating the error, the controller decides when to change the tap position (MV) and by how much. When the controller fir

17、st turns the valve on, they may turn the hot valve only slightly if warm water is desired, or they may open the valve all the way if very hot water is desired. This is an example of a simple proportional control. In the

18、event that hot water does not arrive quickly, the controller may try to speed-up the process by opening up the</p><p>　　In the interest of achieving a gradual convergence at the desired temperature (SP), the

19、 controller may wish to dampthe anticipated future oscillations. So in order to compensate for this effect, the controller may elect to temper their adjustments. This can be thought of as a derivative control method.<

20、/p><p>　　Making a change that is too large when the error is small is equivalent to a high gain controller and will lead to overshoot. If the controller were to repeatedly make changes that were too large and r

21、epeatedly overshoot the target, the output would oscillate around the setpoint in either a constant, growing, or decaying sinusoid. If the oscillations increase with time then the system is unstable, whereas if they decr

22、ease the system is stable. If the oscillations remain at a constant magnitude t</p><p>　　If a controller starts from a stable state at zero error (PV = SP), then further changes by the controller will be in

23、response to changes 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. Generally contr

24、ollers are used to reject disturbances and/or implement setpoint changes. Changes in feed water temperature constitute a disturbance to the faucet temperature con</p><p>　　In theory, a controller can be used

25、 to control any process 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 tempera

26、ture, pressure, flow 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>

27、<p>　　PID controllers are the controllers of choice for many of these applications, due to their well-grounded theory, established history, simplicity, and simple setup and maintenance requirements.</p><

28、;p><b>　　History </b></p><p>　　PID controllers date to 1890s governor design.[1][5] PID controllers were subsequently developed in automatic ship steering. One of the earliest examples of a PID

29、-type controller was developed by Elmer Sperry in 1911,[6] while the first published theoretical analysis of a PID controller was by Russian Americanengineer Nicolas Minorsky, in (Minorsky 1922). Minorsky was designing a

30、utomatic steering systems for the US Navy, and based his analysis on observations of ahelmsman, observing that the hel</p><p>　　Initially controllers were pneumatic, hydraulic, or mechanical, with electrical

31、 systems later developing, with wholly electrical systems developed following World War II.</p><p>　　Minorsky's work</p><p>　　In detail, Minorsky's work proceeded as follows.[8] His goa

32、l was stability, not general control, which significantly simplified the problem. While proportional control provides stability against small disturbances, it was insufficient for dealing with a steady disturbance, notab

33、ly a stiff gale (due to droop), which required adding the integral term. Finally, the derivative term was added to improve control. Trials were carried out on the USS New Mexico, with the controller controlling the angul

34、a</p><p>　　Limitations of PID control</p><p>　　While PID controllers are applicable to many control problems, and often perform satisfactorily without any improvements or even tuning, they can p

35、erform poorly in some applications, and do not in general provide optimalcontrol. The fundamental difficulty with PID control is that it is a feedback system, with constant parameters, and no direct knowledge of the proc

36、ess, and thus overall performance is reactive and a compromise – while PID control is the best controller with no model of the proces</p><p>　　The most significant improvement is to incorporate feed-forward

37、control with knowledge about the system, and using the PID only to control error. Alternatively, PIDs can be modified in more minor ways, such as by changing the parameters (either gain scheduling in different use cases

38、or adaptively modifying them based on performance), improving measurement (higher sampling rate, precision, and accuracy, and low-pass filtering if necessary), or cascading multiple PID controllers.</p><p>　

39、　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 about the control setpoint value. They also have diffi

40、culties in the presence of non-linearities, may trade off regulation versus response time, do not react to changing process behavior (say, the process changes after it has warmed up), and have lag in responding to large

41、disturbances.</p><p><b>　　Linearity</b></p><p>　　Another problem faced with PID controllers is that they are linear, and in particular symmetric. Thus, performance of PID controllers

42、 in non-linear systems (such as HVAC systems) is variable. For example, in temperature control, a common use case is active heating (via a heating element) but passive cooling (heating off, but no cooling), so overshoot

43、can only be corrected slowly – it cannot be forced downward. In this case the PID should be tuned to be overdamped, to prevent or reduce overshoot,</p><p>　　Noise in derivative</p><p>　　A proble

44、m with the Derivative term is that small amounts of measurement 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 h

45、igher-frequency noise components. However, low-pass filtering and derivative control can cancel each other out, so reducing noise by instrumentation means is a much better choice. Alternatively, a nonlinear median filter

46、 may be used, which improves the filtering efficienc</p><p>　　Feed-forward</p><p>　　The control system performance can be improved by combining the feedback (or closed-loop) control of a PID con

47、troller with feed-forward (or open-loop) control. Knowledge about the system (such as the desired acceleration and inertia) can be fed forward and combined with the PID output to improve the overall system performance. T

48、he feed-forward value alone can often provide the major portion of the controller output. The PID controller can be used primarily to respond to whatever difference or er</p><p>　　For example, in most motion

49、 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 loop PID controller is being used to control the speed of

50、 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 that value appropriately and add it to the output of th

51、e PID velocity loop controller.</p><p>　　This means that whenever the load is being accelerated or decelerated, a proportional amount of force is commanded from the prime mover regardless of the feedback val

52、ue. The PID loop in this situation uses the feedback information to effect any increase or decrease of the combined output in order to reduce the remaining difference between the process setpoint and the feedback value.

53、Working together, the combined open-loop feed-forward controller and closed-loop PID controller can provide a more</p><p>　　Other improvements</p><p>　　In addition to feed-forward, PID controlle

54、rs are often enhanced through methods such as PID gain scheduling(changing parameters in different operating conditions), fuzzy logic or computational verb logic [10] [11] . Further practical application issues can arise

55、 from instrumentation connected to the controller. A high enough sampling rate, measurement precision, and measurement accuracy are required to achieve adequate control performance.</p><p>　　Cascade control&

56、lt;/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 PID control. In cascade control there are t

57、wo 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 level or velocity. The other controller act

58、s as inner loop controller, which reads the output of outer loop controller as set</p><p>　　Physical implementation of PID control</p><p>　　In the early history of automatic process control the

59、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 pneumaticcontrollers were once the industry standard.&

60、lt;/p><p>　　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 complex electronic syst

61、ems, for example, the head positioning of a disk drive, the power conditioning of a power supply, or even the movement-detection circuit of a modern seismometer. Nowadays, electronic controllers have largely been replace

62、d by digital controllers implemented with micro controllers or FPGAs.</p><p>　　Most modern PID controllers in industry are implemented in programmable logic controllers (PLCs) or as a panel-mounted digital c

63、ontroller. Software implementations have the advantages that they are relatively cheap and are flexible with respect to the implementation of the PID algorithm.</p><p>　　Variable voltages may be applied by t

64、he time proportioning form of Pulse-width modulation (PWM) – a cycle time is fixed, and variation is achieved by varying the proportion of the time during this cycle that the controller outputs +1 (or ?1) instead of 0.

65、On a digital system the possible proportions are discrete – e.g., incrementsof.1second within a 2 second cycle time yields 20 possible steps: percentage increments of 5% – so there is a discretization error, but for high

66、 enough time resolution</p><p>　　Ideal versus standard PID form</p><p>　　The form of the PID controller most often encountered in industry, and the one most relevant to tuning algorithms is the

67、standard form. In this form the Kp gain is applied to the Iout, and Dout terms, yielding: </p><p><b>　　Where</b></p><p>　　Ti is the integral time</p><p>　　Td is the der

68、ivative time</p><p>　　In the ideal parallel form, shown in the controller theory section</p><p>　　the gain parameters are related to the parameters of the standard form through and . This paral

69、lel form, where the parameters are treated as simple gains, is the most general and flexible form. However, it is also the form where the parameters have the least physical interpretation and is generally reserved for th

70、eoretical treatment of the PID controller. The standard form, despite being slightly more complex mathematically, is more common in industry.</p><p>　　Laplace form of the PID controller</p><p>　

71、　Sometimes it is useful to write the PID regulator in Laplace transform form:</p><p>　　Having the PID controller written in Laplace form and having the transfer function of the controlled system makes it eas

72、y to determine the closed-loop transfer function of the system.</p><p>　　Series/interacting form</p><p>　　Another representation of the PID controller is the series, or interacting form</p>

73、;<p>　　where the parameters are related to the parameters of the standard form through</p><p><b>　　, , and</b></p><p><b>　　With</b></p><p><b>　　

74、.</b></p><p>　　This form essentially consists of a PD and PI controller in series, and it made early (analog) controllers easier to build. When the controllers later became digital, many kept using the

75、 interacting form.</p><p>　　Discrete implementation</p><p>　　The analysis for designing a digital implementation of a PID controller in a Microcontroller (MCU) or FPGA device requires the standa

76、rd form of the PID controller to be discretised [12]. Approximations for first-order derivatives are made by backward finite differences. The integral term is discretised, with a sampling time Δt,as follows,</p>&

77、lt;p>　　The derivative term is approximated as,</p><p>　　Thus, a velocity algorithm for implementation of the discretised PID controller in a MCU is obtained by differentiating u(t), using the numerical de

78、finitions of the first and second derivative and solving for u(tk) and finally obtaining:</p><p><b>　　二、英文翻譯</b></p><p><b>　　PID控制器</b></p><p>　　一個比例，積分，微分控制

79、（PID控制器 ）是一個通用的控制回路，反饋控制器被廣泛應(yīng)用于工業(yè)控制系統(tǒng)，一個PID是最常用的反饋控制器。 PID控制器計算出“一個誤差，一個衡量”值之間的差額作為過程變量和期望的設(shè)定值。該控制器試圖盡量減少調(diào)整過程中控制輸入的錯誤。在這個過程中缺乏基本的控制，PID控制器是最好的控制器。然而，最佳的性能是通過PID參數(shù)的計算中得到的，必須根據(jù)參數(shù)調(diào)整系統(tǒng)的性質(zhì)，工程設(shè)計是通用的，參數(shù)依賴于特定的系統(tǒng)。</p><

80、p>　　PID控制器計算（算法）涉及三個不同的參數(shù)，因此有時也被稱為三參數(shù)控制：比例的積分和導(dǎo)數(shù)的值，記為P，I和 D的比例值確定的誤差反應(yīng)，電流，最近的積分值確定誤差的反應(yīng)總結(jié)的基礎(chǔ)上，和衍生工具的價值確定在發(fā)生變化有反應(yīng)的基礎(chǔ)上的速度的錯誤。 這三項行動的加權(quán)總和，是用來調(diào)整通過如控制閥或加熱元件的電源控制元素的位置的過程。 啟發(fā)式，這些值可以在時間上的解釋：P更改取決于當前的錯誤，I自己過去的積累誤差，D是未來的一個預(yù)測的誤

81、差，根據(jù)目前的速度。</p><p>　　通過調(diào)整算法在PID控制器的三個常量，該控制器可以控制行動提供具體的工藝要求設(shè)計的。 該控制器的反應(yīng)可以說是在控制器方面的反應(yīng)的一個錯誤，在何種程度上控制過沖和振蕩的設(shè)定值學位制度。 請注意控制使用的PID算法并不能保證最優(yōu)控制系統(tǒng)或系統(tǒng)的穩(wěn)定性。</p><p>　　有些應(yīng)用程序可能需要使用一個或兩個模式，以提供適當?shù)南到y(tǒng)控制。 這是通過設(shè)置參數(shù)

82、的控制輸出到零增長。 將PID控制器將被稱為可調(diào)控制，把P或I的行動控制器控制的情況下各自。 PI控制器是相當普遍的，因為衍生訴訟是敏感的測量噪聲值，而積分的情況下一個可能會阻止系統(tǒng)從實現(xiàn)其目標價值由于管制行動。</p><p><b>　　控制回路基礎(chǔ)知識</b></p><p>　　一個熟悉的例子是控制回路時采取調(diào)整冷熱水龍頭閥門保持在理想的溫度水龍頭水的行動。

83、這通常涉及到兩個進程混合流，熱水和冷水。 此人觸及的水感或測量其溫度。 在此基礎(chǔ)上，他們執(zhí)行的反饋控制作用，以調(diào)節(jié)溫度，直到該進程的熱水和冷水閥穩(wěn)定在所需的值。</p><p>　　水溫傳感采取了類似的程序的價值或過程變量（PV）的測量。 所需的溫度稱為設(shè)定點（SP法）。 在這一進程（水閥門的位置）被稱為操縱變量（MV）的投入。 之間的溫度測量和設(shè)定點的區(qū)別是錯誤（e）條，量化的水是否過熱或過冷和多少。</

84、p><p>　　經(jīng)過測量溫度（光伏），然后計算錯誤，控制器決定何時改變水龍頭位置（MV）和多少。 當?shù)谝淮未蜷_控制器上的閥門，他們可能把熱閥僅略有如果溫水是理想，或者他們可能會打開閥門，如果所有的方式是非常理想的熱水。 這是一個例子，一個簡單的控制比例 。 假如熱水不到位迅速，控制器可能會嘗試的加速通過開放更多的熱水閥門和，隨著時間的推移，更多的進程。 這是一個例子，一個完整的控制。 只使用比例和積分控制方法，它有可

85、能在某些系統(tǒng)中水的溫度可能會冷熱之間搖擺不定，因為該控制器調(diào)節(jié)閥過快和過補償或過度調(diào)整的設(shè)定點。</p><p>　　在SP利益所需要的溫度（實現(xiàn)逐步趨同的），控制器不妨潮濕預(yù)計未來振蕩。 因此，為了彌補這方面的影響，該控制器可以選擇鍛煉的調(diào)整。這可以被認為是一個衍生的控制方法。</p><p>　　制作一個變化太大時，誤差小，相當于一個高增益控制器，將導(dǎo)致過沖。 如果控制器要反復(fù)進行修改

86、體積過大，反復(fù)沖的目標，產(chǎn)出將振蕩周圍不斷在任一給定值，成長或腐爛的血竇 。 如果振蕩隨時間增加，然后系統(tǒng)是不穩(wěn)定的，而如果他們降低了系統(tǒng)穩(wěn)定。 如果振蕩系統(tǒng)維持在一個恒定幅度是輕微的穩(wěn)定 。 一個人不會這么做，因為我們是自適應(yīng)控制器 ，歷史學習的過程，但是，簡單的PID控制器沒有學習的能力，必須正確設(shè)置。 為有效控制，選擇正確的收益被稱為校正控制器。</p><p>　　如果一個控制器開始從穩(wěn)定狀態(tài)零誤差（光伏

87、= SP法），然后由控制器將在進一步修改反應(yīng)到其他測量或不可測量輸入的變化過程，對過程的影響，進而對光伏。 變量的進程的影響比其他的MV被稱為干擾。 一般來說控制器是用來拒絕干擾和/或執(zhí)行設(shè)定點的變化。 在給水溫度變化構(gòu)成的滋擾水龍頭溫度控制過程。</p><p>　　從理論上講，一個控制器可以用來控制任何過程，有一個可衡量的產(chǎn)出（光伏），一個著名的輸出（SP）和一個輸入理想值的過程（中壓），將影響到有關(guān)光伏。

88、控制器是用于工業(yè)，以調(diào)節(jié)溫度，壓力，流量，化學組成， 速度和其他幾乎每一個測量變量的存在。 汽車巡航控制系統(tǒng)控制的例子是一個過程，利用自動化。</p><p>　　PID控制器是許多此類應(yīng)用的首選控制器，由于其良好的基礎(chǔ)理論，建立了歷史，簡單，而簡單的安裝和維修的要求。</p><p><b>　　歷史</b></p><p>　　PID控制器

89、是在1890提出來的。后來發(fā)展PID控制器在船舶自動轉(zhuǎn)向。 一個控制器PID型最早開發(fā)的一個例子，在1911年，由埃爾默斯佩里而首次發(fā)表的PID控制器的理論分析是一個由俄羅斯的美國工程師尼古拉米諾爾斯基 ，在（ 米諾爾斯基1922年 ）。 米諾爾斯基是美國海軍設(shè)計的自動轉(zhuǎn)向系統(tǒng)，并根據(jù)他的分析意見上的舵手 ，并指出當前錯誤的舵手控制船舶的基礎(chǔ)上，不僅，而且也對過去的錯誤和改變目前的速度; 這是當時由米諾爾斯基數(shù)學。 海軍最終沒有采用該系

90、統(tǒng)，是由于工作人員的抵制。 類似的工作是進行搶修，在20世紀30年代出版的幾個人。</p><p>　　最初控制器是氣動，液壓或機械，電氣系統(tǒng)與后來發(fā)展的系統(tǒng)，開發(fā)全電動以下第二次世界大戰(zhàn) 。具體而言，米諾爾斯基的工作進展如下。他的目標是穩(wěn)定的，不是一般的控制，大大簡化了問題。 雖然比例控制提供了對小擾動穩(wěn)定，這是干擾不夠穩(wěn)定的處理一個，特別是硬大風（由于下垂），需要加入積分項。 最后，導(dǎo)數(shù)項的加入，以加強控制。

91、試驗共進行了關(guān)于新墨西哥號 ，與該控制器控制角速度 （不舵角）的。PI控制取得了持續(xù)的偏航（角誤差為± 2 °，同時增加四）取得的± 1 / 6偏航°，比大多數(shù)舵手更可能實現(xiàn)。</p><p><b>　　PID控制的局限性</b></p><p>　　PID控制器，適用于多種控制問題，往往表現(xiàn)欠佳，沒有任何改善，甚至調(diào)整，他們

92、可以在一些應(yīng)用中表現(xiàn)不佳，不一般提供最優(yōu)控制 。 PID控制的基本困難的是，這是一個反饋系統(tǒng)， 不斷參數(shù)，并沒有直接的知識的過程，因此整體表現(xiàn)反應(yīng)和妥協(xié)- PID控制，而這個過程是最好的無模型控制器， [1]獲得更好的性能，可通過整合過程模型的研究。</p><p>　　最顯著的改善，是將有關(guān)系統(tǒng)的知識與前饋控制，只用了PID控制誤差。 此外，PID能以更多方式進行修改，未成年人如通過改變參數(shù)（或增益調(diào)度在不同的

93、使用情況或基于自適應(yīng)地修改它們的性能），提高測量（高采樣率，精度和準確度，和低通必要時過濾），或級聯(lián)多個PID控制器。</p><p>　　PID控制器，當單獨使用，可以提供性能不佳時，PID回路增益必須減少，使控制系統(tǒng)不會過沖，振蕩或狩獵有關(guān)控制設(shè)定點值。 他們也有在非線形性存在困難，可能會權(quán)衡調(diào)控與響應(yīng)時間，也不會改變反應(yīng)過程的行為（也就是說，過程更改后，升溫），并在應(yīng)對大規(guī)模騷亂滯后。</p>

94、<p><b>　　線性</b></p><p>　　與PID控制器面臨的另一個問題是，它們是線性的，特別是對稱的。 因此，中PID控制器性能的非線性系統(tǒng)，（如HVAC系統(tǒng) ）是可變的。 例如，在溫度控制，共同積極加熱用例通過加熱元件（），但被動冷卻（加熱過，但沒有冷卻），因此只能予以糾正超調(diào)慢 - 它不能被強迫下降。 在這種情況下，應(yīng)調(diào)整的PID為過阻尼，以防止或減少過沖，雖然

95、這會降低性能（它增加沉淀時間）。</p><p><b>　　噪音</b></p><p>　　一個長遠的問題是，與衍生或過程少量測量噪聲可能會導(dǎo)致在輸出大數(shù)量的變化。 它往往是一個有益的濾波器的測量低通濾波器 ，以消除更高頻率的噪聲成分。 然而，低通濾波及衍生控制可以相互抵消，從而減少了儀器噪聲手段是更好的選擇。 另外，一個非線性中值濾波可以使用，提高了過濾效率和實

96、際表現(xiàn)[9] 。 在某些情況下，帶差很多，可以打開系統(tǒng)關(guān)閉與對照小的損失。 這相當于使用控制器的PID作為有價證券控制器。</p><p><b>　　前饋</b></p><p>　　該控制系統(tǒng)的性能可提高相結(jié)合的反饋 （或閉環(huán)）與控制的PID控制器的前饋 （或開環(huán)）控制。 知識的系統(tǒng)（如預(yù)期的加速度和慣性）可喂養(yǎng)著與PID的輸出相結(jié)合，提高整體系統(tǒng)性能。 前饋價值

97、往往可以提供單獨的控制器輸出的主要部分。 PID控制器，可主要用于應(yīng)付任何差異或錯誤 ）之間仍然存在的設(shè)定點（SP）和（PV中的實際價值的過程變量。 由于前饋輸出不是由進程的反饋影響，但絕不能導(dǎo)致控制系統(tǒng)振蕩，從而提高了系統(tǒng)響應(yīng)和穩(wěn)定性。</p><p>　　例如，在大多數(shù)運動控制系統(tǒng)，以加速控制的機械負荷，更具影響力或扭矩是從原動機，電機，或執(zhí)行器所需。 如果速度回路PID控制器被用于控制負載的速度和指揮力或力

98、矩受到原動力應(yīng)用，那么它有利于采取瞬時加速度的負載需要，規(guī)模適當，并將其添加值到速度環(huán)的PID控制器的輸出。 這意味著，每當負荷正在加速或減速，按比例計算的武力是從原動力指揮不論反饋的價值。 在這種情況下使用PID回路的反饋信息進行任何增加或合并后的減產(chǎn)，以減少過程之間的設(shè)定值和反饋值的差額。 攜手合作，聯(lián)合開環(huán)前饋控制和閉環(huán)PID控制器可以提供一個更加靈活，穩(wěn)定，可靠的控制系統(tǒng)。</p><p><b&g

99、t;　　其他改進</b></p><p>　　除了前饋，PID控制器的方法往往是通過增強如PID 增益調(diào)度的條件（在不同的操作參數(shù)的變化）， 模糊邏輯或邏輯運算動詞。進一步的實際應(yīng)用可能出現(xiàn)的問題從連接到控制器儀器。 足夠高的采樣率，測量精度和測量精度必須達到足夠的控制性能。</p><p><b>　　串級控制</b></p><p&

100、gt;　　PID控制器的一個突出的優(yōu)點是，兩個PID控制器一起使用，可以產(chǎn)生更好的動態(tài)性能。 這就是所謂的級聯(lián)PID控制。 在串級控制安排有一兩個的PID PID控制的另一個設(shè)置點。 作為外回路控制器，控制液面，或如速度的主要物理參數(shù)，PID控制器的行為。 作為內(nèi)環(huán)控制器，讀取外部回路控制器的輸出作為其他控制器設(shè)置點，通?？刂聘涌焖僮兓膮?shù)，流量或加速行為。 它可以證明[ 該控制器的工作頻率的增加和時間常數(shù)的對象是減少使用級聯(lián)控制器