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外文资料翻译

外文资料翻译
外文资料翻译

System Design an Compensation Techniques

Control systems are designed to perform specific tasks.The requirements imposed on the control system are usually referred as performance imposed on the control system are usually referred as performance specifications.They generally relate to accuracy,relative stability and speed of response.

Generally,the performance specifications should not be more stringent than necessary to perform the given task.If the accurary at steady-state operation is of prime importance in a given control system,then we should not require unnecessarily rigid performance specifications on the transient response since such specifications will require expensive components.We should remember that the most important part of control system design is to state the performance specifications precisely so that they will yield an optimal control system for a given purpose.

In this lesson,we are going to briefly introduce the design and compensation procedure of single-input-single-output-(SISO),linear time-invariant (LTI) control systems by the frequency response and root-locus approaches,Compensation is the modification of the modification of the system dynamics to satisfy the given specifications.

Setting the gain is the first step in adjusting the system for satisfactory performance.In many cases,increasing the gain value will improve the steady-state behavior but will result in poor stability or even instability,Then it is necessary to redesign the system (by modifying the structure or by incorporating additional devices or components) to alter the overall behavior so that the system will behave as desired.

Fig.8.1 shows the configuration where the compensator G(s) is placed in series with the plant.This scheme is called series compensation. Another kind or compensation is feedback compensation.Generally,series compensation may be simpler than feedback compensation,

In discussing compensators,we frequently use terminology as lead network,and lag-lead network.If a sinusoidal input ei is applied to the input of a network and the steady-state output e0 (which is also sinusoidal) has a phase lead,then the network is called a lead network.Similarly, if the steady-state output e0 has a phase lag,then the network is called a lag network.In a lag-lead network,phase lag and phase lead both occur in the output but in different frequency regions;phase lag occurs in the low-frequency region and phase lead occurs in the high-frequency region.

The root-locus method is a graphical method for determining the locations of all closed-loop poles from knowledge of the locations of the locations of the open-loop poles and zeros as some parameter(usually the gain) is varied from zero to infinity.The method yields a clear indication of effects of parameter adjustment.In practice,the root-locus plot of a system may indicate that the desired performance cannot be achieved just by the adjustment of gain.Then it is necessary to reshape the root loci to meet the performance specifications.

In designing a control system,we may modify the original root loci by inserting a suitable compensator Gc(s) (as shown in Fig.8.1).Once the effects on the root locus of the addition of the poles and/or zeros are fully understood,we can readily determine the locations of the pole(s) and zero(s) of the compensator that will reshape the root locus as desired.In the design by the root-locus method,the root-loci of the system are reshaped through the use of a compensator so that a pair of dominant closed-loop poles can be placed at the desired locations.(Usually,the damping ratio and undamped natural frequency may be specified by the location of a pair of dominant closed-loop poles.)

The addition of a pole to the open-loop transfer function has the effect of pulling the root locus to the right,tending to lower the system's relative stability and to slow down the settling of the response.The addition of a zero has the effect of pulling the root locus to the left,tending to make the system more stable and to speed up the settling of the response.

The root-locus approach to design is very powerful when the specifications are given in term

of time domain quantities,such as the damping ratio and undamped natural frequency,maximum overshoot,rise time and setting time.

Let us consider a design problem.The original system either is unstable for all values of gain or is stable but has undesirable transient response characteristics.In this case,the reshaping of the root locus is necessary in order that the dominant closed-loop poles be at desired locations in the complex plane.Inserting an appropriate lead compensator in cascade with the feed-forward transfer function may solve this problem.

It is important to note that in a control system design,transient-reponse performance is usually most important.In the frequency-response approach,we specify the transient-response in term of the phase and gain margin,resonant peak magnitude,the gain crossover frequency,resonant frequency response is indirect,the frequency domain specification can be met conveniently by means of Bode diagram.

Design in the frequency domain is simple and straightforward.After the open loop has been designed by frequency response method,the closed loop poles and zeros can be determined.The transient response characters must be checked to see whether the designed system meets the requirements in the time domain.If it does not,the compensator has to be modified and the analysis must be repeated until a satisfactory result is obtained.

Basically,there are two approaches in the frequency-domain design.One is the polar plot approach and the other is the Bode diagram approach.It is more convenient to work with Bode diagram.A Bode diagram of the compensator can be simply added to the original Bode diagram,and thus plotting the complete Bode diagram is a simple matter.Also,if the open loop gain is varied,the magnitude curve is shifted up or down without changing the slope of the curve,and the phase curve remains the same.

A common approach to the Bode diagram is that we first adjust the open loop gain so that the requirement on the steady state accuracy is met.Then we plot the magnitude and phase curves of the uncompensated open loop.If the specification on the phase margin and gain margin are not satisfied,then a suitable compensator that will reshape the open loop transfer function is determined.

In many practical cases,compensation is essentially a compromise between steady-state accuracy and relative stability.In order to have a high value of the velocity error constant and yet satisfactory relative stability,we find it necessary to reshape the open loop frequency response curve.The gain in the low-frequency region should be large enough to satisfy the steady-state accuracy requirements.For the medium-frequency region (near the gain crossover frequency wc from both directions),the slope of the log-magnitude curve in the Bode diagram should be -20dB per decade. This slope should extend over a sufficient wide frequency band to assure a proper phase margin.For the high-frequency region,the gain should be attenuated as rapidly as possible to minimize the effects of noise.

The basic characteristics of lead,lag,and lag-lead compensation are as following.lead compensation essentially yields an appreciable improvement in transient response and a small change in steady-state accuracy.It may accentuate high-frequency noise effects.On the other hand ,lag compensation yields an appreciable improvement in steady-state accuracy at the expense of increasing the transient-response https://www.doczj.com/doc/8816907724.html,g compensation will suppress the effects of high-frequency noise https://www.doczj.com/doc/8816907724.html,g-lead compensation combines the characteristics of both lead compensation and lag compensation.

Discrete-time Systems and the z-Transform Method Discrete-time systems,or sampled-data system,are dynamic systems in which one or more variables can change only at discrete instants of time.These intstants,which we shall denote by kt or tk(k=0,1,2,........),may specify the time at which some physical measurement is performed or the time at which the memory of a digital computer is read out,etc.The time interval between these discrete instants can be approximated by simple interpolation.

Discrete-time systems differ from continuous-time ones in that the signals for a discrete-time system are in sample-data form.

Discrete-time systems arise in practice whenever the measurements neccessary for control are obtained in an intermittent fashion,or a large scale controller or computer is time-shared by several plants so that a control signal is sent out to each plant only periodically or whenever a digital computer is used to perform computations necessary for control.Many modern industrial control systems are in time.Sometimes,however,sampling operation,or discretization may be entirely fictitious and introduced only to simplify the analysis of control system which actually contains only continuous elements.whose inputs and/or outputs are in time.Sometimes,however,sampling operation,or discretization,may be entirely fictitious and introduced only to simplify the analysis of control system which actually contain only continuous elements.

In this lesson,we shall be concerned with discrete-time systems which the signal representing the control efforts is piecewise constant and changes only st discrete points in time.Since there are several different types of sampling operation of practical importance,we shall list them as follows:

(1)Periodic(conventional) sampling:In this case,the sampling instants are equally spaced,or tk=kt(k=1,2,3....)

Multiple-order sampling:The pattern of the tk is repeated periodically,or tk+r - tk=constant for all k.

Multiple-order-rate sampling:In this case,two concurrent sampling operations occur at tk=pT1 and qT2,where T1,T2 are contants and p ,q are integers.

Random sampling:In this case,the sampling instants are random,or tk is a random variable. Here we shall treat only the case which the samplng is periodic.

Quantization.The inclusion of digital computer in an otherwise analog system produces in digital form(usually as binary numbers) in part of the system.The system then takes the form of a mixed digital-analog combination.The introduction of a digital computer in a control system requires the use of digital-to-digital converters.The conversion of an analog signal to the corresponding digital signal(binary number)is an approximation because the analog signal can take an infinite number of values,whereas the variety of different numbers which can be formed by a finite number of values,whereas the variety of different numbers which can be formed by a finite set of digits is limited.This approximation process is called quantization. The process of quantizing (converting a signal in analog form to digital form)may be fulfilled by means of some specific circuits.The range of input magnitudes is divided into a finite number of disjoint intervals hi which are not necessarily equal.All magnitudes fallinjg within each interval are equated to a single value within the interval.This single value is the digital approximation to the magnitudes of the analog input signal.Thus,if x si the analog input,the digital output is given by y=Q(x )

Where Q is the quantizing function.

The function x(t) is a discrete-time function.The operation of digital control systems involves quantization both in amplitude and in time.We s hall next present the definitions of several terms.

Transducer.A transducer is a device which converts an input signal into an output signal of another form.(The output signal.in general,depends on the past history of the input).

Analog transducer.An analog transducer is a device which converts an input signal into an ouput signals occur only at discrete instants of time (usually periodic),but the magnitudes of these signals may be any value within the physical limitations of the system.

Sampled-data transducer.This is a transducer in which the input and output signals occur only at discrete instants of time(usually periodic),but the magnitudes of the signal,as in the case of the analog transducer,are unquantized.

Digital transducer.A digital transducer is one in which the input signal is a continuous function of time and the output signal is a quantized signal which can assume only certain discrete levels.

Analog-to-digital transducer.A digital-to-analog transducer is one in which the input signal is a quantized signal and the output signal is a smoothed continuous function of time.

Analog controllers and digital controllers.In considering the types of controllers which are used in industrial control system,we may divide them into the following three categories: Analog controllers or computers:Analog controllers or computer represent the variables in the equations by continuous physical quantities.Analog controllers can be designed which will satisfactorily serve as nondecision making controllers.

Digital controllers or computers:These operate only on numbers.Decision-making is an important function in digital controllers,and they are currently being used for the solution of problems

Involving the optimal overall operation of industrial plants.

Analog-digital controllers or computers:These are often called hybrid controllers.They are combinations of amalog controllers and digital controllers.Some of high performance controllers are of this type.

Advantages of digital controllers over analog controller.Some of the advantages of digital controllers over amalog controllers may be summarized as follows:

(1)Digital controllers are capable of performing complex computations with constant accuracy at high speed.Digital computers can have almost any desired accuracy in computations at relatively little increase in cost.On the other hand,the cost of analog computers increases rapidly as the complexity of the computations increase if constant accuracy is to be maintained.

(2)Digital controllers are extremely versatile. By merely issuing a new program,one can completely change the operations being performed.This feature is particularly important if the control system is to receive operating information or instructions from some computing center,where economic analysis and optimization studies are being made.

Because of the inability of conventional techniques to adequately handle complex control problems,it has been customary to subdivide a process into smaller units and handle each of these as a separate control problem. Human operators are normally used to coordinate the operation of units.Recent advances in computer control systems have caused changes in this use of industrial process controls.Recent developments in large-scale computers and mathematical methods provide a basis for use of all available information in the control system.In conventional control,this part of the control loop is being done directly by humans. Computer control of complex systems.Current trends in the control of large-scale systems are to consolidate the multiplicity of independently controlled units into single optimally controlled processes.In industrial process control system,it is,in general,not practical to operate for a very long time at steady state because certain changes in production requirements,raw materials,economic factors,and processing equipment and techniques,may occur.Thus,the transient behavior of industrial processes must be taken into consideration.Since there are interactions among process variable,using only one process variable for each control agent is not suitable for really complete control.By use of computer control,it is possible to take into account all process variables together with economic factors,production requirements,equipment performance,etc..,and to thereby accomplish optimal control of industrial processes.

Note that a system capable of controlling a process as completely as possible will have to solve complex equations.The more complete the control of industrial processes.

Note that a system capable capable of controlling a process as completely as possible will have to solve complex equations.The more complete the control,the more important it is that

the correct relations between operating variables be known and be used.The system must be capable of accepting instructions from such varied sources as computer and human operators and must also be capable of changing its control subsystem completely in a short time.

Introductions to PID controllers

PID controllers can be stand-alone controllers (also called songle loop controllers), controllers in PLCs, embedded controllers, or software in Visual Basic or C# computer programs.

PID controllers are process controllers with the following characteristics:

·Continuous process control

·Analog output(also known as “measurement” or “Process Variable” or “PV”)

·Analop output (referred to simply as “output”)

·Setpoint(SP)

·Proportional(P), Integral(I), and/or Derivative(D) constants

Examples of “continuous process control” are temperature, pressure, flow, and level control. For example, controlling the heating of a tank. For simple control, you have temperature limit sensors(one low and one high) and then switch the heater on when the low temperature limit sensor turns on and then turn the heater off when the temperature rises to the high temperature limit sensor. This is similar to most home air conditioning & heating thermostats.

In contrast, the PID controller would receive input as actual temperature and control a valve that regulates the flow of gas to the heater, The PID controller automatically finds the correct (constant) flow of gas to the heater that kepps the temperature steady at the setpoint. Instead of the temperature bouncing back and forth between two points, the temperature is held steady. If the setpoint is lowered, then the PID controller automatically reduces the amount of gas flowing to the heater. If the setpoint is raised, then the PID controller automatically increases the amount of gas flowing to the heater. Likewise the PID controller would automatically for hot, sunny days (when it is hotter outside the heater) and for cold, cloudy days.

The analog input (measurement) is called the “process variable” or “PV”. You want the PV to be a highly accurate indication of the process parameter you are trying to control. For example, if you want to maintain a temperature of + or – one degree then we typically strive for at least ten times that or one-tenth of a degree. If the analog input is a 12 bit analog input and the temperature range for the sensor is 0 to 400 degrees then our “theoretical”accuracy is calculated to be 400 degrees divided by 4,096 (12bit) =0.09765625 degrees. We say “theoretical” because it would assume there was no noise and error in our temperature sensor, wiring, and analog converter. There are other assumptions such as linearity, etc .. The point being-with 1/10 of a degree “theoretical” accuracy should easily be attainable.

The analog output is often simply referred to as “output”. Often this is given as 0~100 percent. In this heating example, it would mean the valve is totally closed (0%) or totally open (100%).

The setpoint (SP) is simply-what process value do you want. In this example-what temperature do you want the process at?

The PID controller’s jod is to maintain the output at a level so that there is no difference (error) between the process variable (PV) and the setpoint (SP)

In Fif.1, the valve could be controlling the gas going to a heater, the chilling of a cooler, the pressure in a pipe, the flow through a pipe, the level in a tank, or any other process control system.

What the PID controller is looking at is the difference (or “error”) between the PV and the SP. It looks at the absolute error and the rate of change of error. Absolute error means- is there a big difference in the PV and SP or a little difference? Rate of change of error means- si the difference between the PV or SP getting smaller or larger as time goes on.

When there is a “process upset”, meaning, when the process variable or the setpoint quickly changes- the PID controller has to quickly change the output to get the process variable back equal to the setpoint. If you have a walk-in cooler with a PID controller and someone opens the door and walk in, the temperature (process variable) could rise very quickly. Therefore the PID controller has to increase the cooling (output) to compensate for this rise in temperature.

Once the PID controller has the process variable equal to the setpoint, a good PID controller wlii not vary the output. You want the output to be very steady (not changing). If the valve (motor, or other control element) is constantly changing, instead of maintaing a constant value, this could cause more wear on the control element.

So there are these two contradictory goals. Fast response (fast change in output) when there is a “process” upset, but slow response (steady output) when the PV is close to the setpoint.

系统设计和补偿技术

控制系统被设计用来执行特定任务。对控制系统的要求通常被称为系统的性能指标。它们通常和系统精确度、相对稳定性及响应速度有关。

一般地,系统的性能指标不应该比系统执行给定任务事所必须达到的指标更加苛刻。对于某一个给定的系统而言,如果稳态运行精度是最为重要的,那么,我们就不应该提出不必要的过高的暂态性能指标要求。满足这些过高的暂态性能指标往往需要昂贵的部件。我们应该牢记,控制系统设计过程中最重要的一个环节就是把性能要求精确的表达出来,这样才会设计出对于给定的任务而言最优的控制系统。

在本课中,我们将要简单的介绍使用频率响应法和跟轨迹法对但输入但输出线性定常系统进行设计和补偿的方法。补偿是指改变系统的动态特性以满足给定的指标。

调节一个系统以得到满意性能的第一步是设定它的增益。在很多情况下,增加增益值将改善系统的稳态性能,但是也将使系统稳定性变差,甚至变得不稳定。于是必须重新设计系统(修改结构或者增加装置或是部件),改变总体特性,使系统按照我们所希望的那样运行。

补偿器G(s)和被控对象串联连接。这种方法称为串联补偿。另外一种补偿是反馈补偿。串联补偿通常比反馈补偿简单。

在讨论补偿器时,我们经常使用的术语是超前网络、滞后网络以及滞后超前网络。如果一个正弦信号ei加到一个网络上,它的稳态输出eo(也是正弦信号)相位超前,则该网络称为超前网络。在滞后超前网络中,相位滞后和相位超前两种情况都会出现,但是出现在不同的频率范围内;相位滞后出现在低频段,相位超前出现在高频段。

跟轨迹法是一种图解的方法。已知开环零点和极点的位置,当某个参数(通常是增益)的值从零变化到无穷大时,可以确定所有可能的闭环极点的位置。本方法清楚地显示出参数调节的效果。实际上,系统的跟轨迹图表明,仅仅通过调节增益并不能获得理想的性能。于是,必须改变跟轨迹的形状来满足性能指标。

在设计控制系统时,我们可以通过插入一个合适的补偿器G(s)来改变原来的跟轨迹。一旦完全了解了增加极点和/或零点对于跟轨迹的影响,我们就可以很方便的确定补偿器零点极点的位置,以使跟轨迹变成我们所希望的形状。在用跟轨迹法设计的过程中,通过使用补偿器改变系统跟轨迹的形状,以使闭环系统一对主导极点位于理想的位置。(通常,阻尼比及无阻尼自然振荡频率是由闭环系统一对主导极点的位置确定的)

在开环传递函数中增加一个极点的效果是把跟轨迹向右推,倾向于降低系统的相对稳定性,并且降低系统的收敛速度。增加一个零点的效果是把跟轨迹向左推,倾向于使系统更加稳定,并且加快系统的响应。

当系统的性能指标以时域的量(如阻尼比及无阻尼自然频率、最大超调量、上升时间

和调节时间)给出时,采用跟轨迹法设计是非常有效的。

让我们考虑一个设计的问题。原系统要么对所有的增益值均不稳定,要么虽然稳定但是动态响应特性不理想。这种情况下必须改变跟轨迹的形状,以使闭环主导极点位于复平面的理想位置上。在前向传递函数中串联插入一个适当的超前补偿器,就可以解决这个问题。

需要注意,在控制系统的设计中,暂态响应性能通常是最重要的。在频率响应法中我们用相角裕量及增益裕量、谐振峰值幅度、增益穿越频率、谐振频率和带宽来表示暂稳态响应。尽管暂态响应和频率响应的相互关系是间接的,但是频域的指标可以由伯德图很方便达到。

频域中的设计简单而直观。当开环系统由频率设计完成后,闭环的零点和极点就可以确定了。必须检查暂态响应特性,以确认设计的系统是否满足时域的要求。如果不满足要求,必须修改补偿器,重新分析,直到获得满意的结果。

频域中的设计主要有两种方法。一种是极坐标图法,另一钟是伯德图法。用伯德图更方便一些。补偿器的伯德图可以简单的加在原伯德图上,因此画完整的伯德图是简单的事。而且,如果改变开环增益,幅值曲线上下移动,曲线的斜率不变,并且相位曲线也保持不变。

用伯德图设计的常用方法是,我们首先调节开环增益,以使稳态精度的要求得到满足。然后,我们画出尚没有校正的开环幅值曲线和相位曲线。如果对于相位裕量和幅值裕量的指标没有满足,就确定一个改造开环传递函数的合适的补偿器。

在多数情况下,补偿实际上是在稳态精度和相对稳定性之间作一个折衷。为了获得较大的速度误差常数以及满意的相对稳定性,我们发现需要重新构造开环频率响应曲线。低频段的增益应该大到满足稳态精度的要求。中频段(从这两个方向靠近幅频曲线的穿越频率wc),伯德图中对数幅频曲线的斜率应该-20dB/dec。这一斜率应该具有足够宽的频率范围,以确保得到适当的相角裕度。对于高频段,幅值曲线应该尽可能快的衰减,以减小噪声的影响。

超前补偿、滞后补偿和滞后超前补偿的基本特性如后面所述。超前补偿对于暂态响应有明显的改进,对稳态精度改进较小。它可能加强高频噪声的影响。另一方面,滞后补偿明显提高了稳态精度,代价是增加了暂态响应时间。滞后补偿会抑制高频噪声信号的影响。滞后超前补偿综合了超前补偿和滞后补偿两者的特点。

离散系统和Z变换

离散系统或数据采样系统是指一个或多个变量仅在离散系统的瞬时变化的动态系统。这些瞬时值可以用KT或Tk表示,指完成测量的时间或者数字计算机内存的读取时间。两个离散时刻的间隔取得很短,这样这些离散时刻之间的数据可以用简单的插值法近似。离散系统不同于连续系统,它的信号是采样数据形式。

在实际应用中,当控制所需要的测量以间断的方式进行时,或者当大型的控制器或计算机被多个控制对象所共享,导致传送到每一个控制对象去的控制信号仅为周期性信号时,或者在采用数字计算机时去完成控制所必需包含的一些输入输出量在时间上的离散器件。当然,采样操作或离散化有时完全是假设,其引进目的仅仅是为了简化实际上只包含连续性元件的控制系统分析。

在本课本中,我们将讨论作为控制作用的信号是断续的常量离散系统,且该常量仅在离散的时间点上变化。因为存在几种不同类型且有使用价值的采样运算,我们就将它们列举如下:

(1)周期(普通)采样:采样时刻的间隔相等,即tk=kT(k=1,2,3)。

(2)多级采样:tk在形式上周期性地出现,即对于所有的k,tk+1-tk=常量。

(3)多速采样:两个同时进行的采样操作分别发生在tk=PT1和tk=qT2。其中p、q是整数,T1、T2是常数。

(4)随机采样:采样时刻是随机的,即tk是随机变量。

这里我们只讨论周期采样的情况。

量化当模拟系统中包含数字计算机时,系统的某一部分就产生数字形式的信号(通常是二进制数)。因此,系统就呈现出数字模拟式的混合结构形式。在控制系统中引入数字计算机,就要使用数模和模数转换器。因为模拟信号具有无穷的数值,而由一组确定的数值表示数的数量是有限的,所以,模拟量信号转换为相应的数字信号(二进制数)是一种近似。这种近似过程称为量化。

量化的过程(将模拟量转化为数字量)由一些特定的电路来完成。输入量的幅值范围被分为许多有限的区间hi,hi不一定相等。一个区间的所有幅值都取区间内唯一值。这个唯一值就是对模拟输入信号幅值的数字近似。因此,如果x为模拟输入,输出的数字值就由y=Q(x)确定,其中Q为量化函数。

函数X(t)是一个离散信号。数字控制系统的操作包括幅值和时间的量化。下面我们介绍一些术语的定义。

转换器:转换器是将输入信号转换为另一种形式输出的装置(输出信号通常取决于输入信号的历史值)。

模拟转换器:模拟转换器是输入和输出信号都是时间的连续函数的转换器。这些信号可以取系统物理限制范围内的任意值。

采样数据转换器:采样数据转换器是输入和输出信号只在离散的瞬间出现的转化器,并且其幅值和模拟转换器的情况一样,未被量化。

数字转换器:数字转换器是输入和输出信号只在离散的瞬间出现的转换器,其幅值是被量化的,即信号只取特定的离散值。

数字模拟转换器:数字模拟转换器的输入信号为量化信号,而输出信号为时间的平滑连续函数。

模拟控制器和数字控制器就工业控制系统中采用的控制器类型而言,我们可以将它们分为以下3类:

模拟控制器或计算机:模拟控制器或计算机是用连续的物理量表示方程中的变量。模拟控制器可以设计为令人满意的非决策控制器。

数字控制器或计算机:它们仅对数字进行操作。决策是数字控制器的一个重要功能。并常用它们来解决工业对象中总体运行的优化问题。

模拟数字控制器或计算:它们通常被称为混合控制器,是模拟控制器和数字控制器的一种组合。一些高性能控制器属于这种类型。

数字控制器相对于模拟控制器的优点数字控制器相对于模拟控制器的优点可以总结如下:

(1)数字控制能以一定精度高速完成复杂的运算。在运算中,数字计算机能在增加较少成本的情况下实现希望的精度。但是,若保持精度不变,运算越复杂,模拟计算机的成本也就越高。

(2)数字控制器具有很好的通用性。仅仅更新一段程序,就能改变现有的操作。如果控制系统接受进行经济分析和优化研究的计算中心发出的操作信息或指令时,这种优点就尤为重要了。

传统的方法不能处理复杂的控制问题,所以它通常是将过程细分为更小的单元,然后分别作为独立的控制问题来处理。人工操作员通常用于协调多个单元的操作。近来,随着计算机控制系统的发展,改变了工业过程控制的这种状况。大型计算机和数学方法的发展为控制系统中利用所有有用信息奠定了基础。传统控制中的这部分控制回路由人工

完成。

复杂系统的计算机控制大规模系统当前的发展趋势是将多个独立控制单元合并为一

个最优的过程。一般来说,由于产品需求、原材料、经济因素、加工设备和方法的变化,工业过程控制系统并不能长时间工作于固定的状态。因此,我们必须考虑工业过程控制系统并不能长时间工作于固定的状态。因此,我们必须考虑工业过程中的动态特性。因为过程变量之间相互影响,所以,每个控制单元只采用一个过程变量,对于真正的全面控制来说是不适当的。通过使用计算机,可以将所有过程变量和经济因素、产品要求、设备性能等都考虑在内,实现工业过程的最优控制。

值得一提的是,一个尽可能全面地控制过程的系统必须能解复杂的方程。越是全面的控制,了解和应用操作变量之间的正确关系就越重要了。系统必须能接收诸如计算机和操作员这样的不同信号源所发出的指令,并且能在短时间内改变其控制的子系统。

离散系统分析的z变换法和状态空间法离散系统的分析可以很容易采用Z变化法和状态空间法中的任意一种。

Z变换与线性定常离散系统的关系,就像是拉氏变换与线性定常连续系统的关系一样。这部分只介绍线性时不变离散系统的Z变换法。

PID控制器的介绍

PID控制器可以是独立控制器(也可以叫做单回路控制器),可编程控制器(PLC)中的控制器,嵌入式控制器或者是用Vb或C#编写的计算机程序设计。

PID控制器是过程控制器,它具有如下特征:

·连续过程控制

·模拟输入(也被称为“测量量”或“过程变量”或“PV”)

·模拟输出(简称为“输出”)

·基准点

·比例、积分以及/或者微分常数

“连续过程控制”的例子有温度、压力、流量及水位控制。例如。控制一个容器的热量。对于简单的控制,你使用两个具有温度限定功能的传感器(一个限定低温,一个限定高温)。当低温限定传感器接通时就会打开加热器,当温度升高到高温限定传感器时就会关闭加热器。这类似于大多数家庭使用的空调及供暖系统的温度自动调节器。

反过来,PID控制器能够接受像实际温度这样的输入,控制阀门,这个阀门能控制进入加热器的气体流量。PID控制器自动地找到加热器中气体的合适流量,这样就保持了温度在基准点稳定。温度稳定了,就不会在高低两点间上下跳动了。如果基准点降低了,PID控制器就会自动降低加热器中气体流量。如果基准点升高,PID控制就hi自动的增加加热器中气体的流量。同样地,对于高温,晴朗的天气(当外界温度高于加热器时)及阴冷,多云的天气,PID控制器都会自动调节。

模拟输入(测量量)也叫做“过程变量”或“PV”。你希望PV能够达到你所孔子过程参数的高精确度。例如,如果我们想要保持温度为+1度或是-1度,我们至少要为此努力,使其精度保持在0.1度。如果是一个12位的模拟输入,传感器的温度范围是从0度到400度,我们计算的理论精确度就是4096除400度=0.097656度。我们之间所以说就是理论上因为我们假定温度传感器,电线及模拟转换器上没有噪音和误差。还有其他的假定。加入,线性等等。及时是有大量的噪音和其他问题,那理论精度的1/10计算,1度精确度的数值应该很容易得到的。

模拟实处经常被简称为“输出”。经常在0%到100%之间给出。早这个热量的例子中,

阀门完全闭(0%),完全打开(100%)。

基准点(SP)很简单,即你想要什么样的过程量。在这个例子中-你想要过程处于怎样的温度。

PID控制器的任务是维持输出在一个程度上,这样在过程变量(PV)和基准点(SP)上就没有偏差(误差)。

在图中魔法门用来控制进入加热器的气体,冷却器的制冷,水管的压力,水管的流量,容量的水位或其他的过程控制系统。

PID控制器所观察的是PV和SP之间的偏差(或误差)。它观察绝对偏差和偏差变换了。绝对偏差就是-PV和SP之间偏差是大还是小。偏差变换率就是-PV和SP之间的偏差随着时间的变化是越来越小还是越来越大。

如果存在过程扰动,即过程变量或基准点变化时—PID控制器就要迅速改变输出,这样过程变量就返回到基准点。如果你有一个PID控制器的可加入的冷冻装置,某个人打开门进入,温度(过程变量)将会迅速升高。因此,PID控制器不得不提高冷度(输出)来补偿这个温度的升高。

一旦过程变量等同于基准点,一个好的PID控制器就不会改变输出。你所要的输出就会稳定(不改变)。如果阀门(发动机或其它控制元件)不断改变,而不是维持恒量,这将造成控制元件更多的磨损。

这样就有了两个矛盾的目标。当有“过程扰动”时能够快速反应(快速改变输出)。当PV接近基准点时就缓慢反应

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