液位控制英文文献403.pdf

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1、The liquid level control system based on ddematlabsimulink Process control is an important application field of automatic technology,it is to point to the level,temperature,flow control process variables,such as in metallurgy,machinery,chemical,electric power,etc can be widely used.Especially liquid

2、 level control technology in real life,played an important role in production,for example,the water supply,civil water tower if low water levels,can affect peoples lives in water;Industrial enterprises with water,if the drainage water drainage or controlled properly or not,in relation to the worksho

3、p of condition;Boiler drum,if the control level boiler is too low,can make level boiler overheating,possible accident;Jing flow,liquid level control tower control accuracy and level of the craft can influence the quality of the products and the cost,etc.In these production field,are basically labor

4、strength or the operation has certain risk nature of work,extremely prone to accidents caused by operating error,the losses,killing manufacturer.Visible,in actual production,liquid level control accuracy and control effects directly affect the factory production cost and economic benefit of safety c

5、oefficient.Even equipment So,in order to ensure safety,convenient operation,you have to research the development of a d v a n c e d l e v e l c o n t r o l m e t h o d s a n d s t r a t e g i e s.The graduation design topic is the liquid level control system based on ddematlabsimulinkforce control,A

6、mong them was controlled object for tank level,Communication mode for DDE communications,Matlab is mainly used in the simulation test,And force control software used for modeling,This system mainly through combination of hardware and software device to achieve precise control of liquid level,In mode

7、rn industry level control of important component,it influence upon production not allow to ignore,in order to ensure safety in production and the product quality and quantity,the level and perform effective control is very necessary,The following is a description of all aspects：一 PID controller A pr

8、oportional integralderivative controller(PID controller)is a generic.control loop feedback mechanism widely used in industrial control systems.A PID controller attempts to correct the error between a measured process variable and a desired set point by calculating and then outputting a corrective ac

9、tion that can adjust the process accordingly.The PID controller 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 reaction based on the sum of re

10、cent errors and the Derivative determines the reaction to the rate at which the error has been changing.The weighted sum of these three actions is used to adjust the process via a control element such as the position of a control valve or the power supply of a heating element.By tuning the three con

11、stants in the PID controller algorithm the PID can provide control action designed for specific 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 set point and the degree

12、 of system oscillation.Note that the use of the PID algorithm for control does not guarantee optimal control of the system or system stability.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 control

13、 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 measurement noise,and the absence of an integral value may prevent the system from reaching

14、its target value due to the control action.1.Control loop basics A familiar example of a control loop is the action taken to keep ones shower 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 temper

15、ature.Based on this measurement they perform a control 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.Feeling the water temperature is taking a measu

16、rement of the process value or process variable(PV).The desired temperature is called the set point(SP).The output from the controller and input to the process(the tap position)is called the manipulated variable(MV).The difference between the measurement and the set point is the error(e),too hot or

17、too cold and by how much.As a controller,one decides roughly how much to change the tap position(MV)after one determines the temperature(PV),and therefore the error.This first estimate is the equivalent of the proportional action of a PID controller.The integral action of a PID controller can be tho

18、ught of as gradually adjusting the temperature when it is almost right.Derivative action can be thought of as noticing the water temperature is getting hotter or colder,and how fast,and taking that into account when deciding how to adjust the tap，Making a change that is too large when the error is s

19、mall 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 repeatedly overshoot the target,this control loop would be termed unstable and the output would oscillate around the set point in either a constant,growin

20、g,or decaying sinusoid.A human would not do this because we are adaptive controllers,learning from the process history,but PID controllers do not have the ability to learn and must be set up correctly.Selecting the correct gains for effective control is known as tuning the controller.If a controller

21、 starts from a stable state at zero error(PV=SP),then further changes by the controller will be in 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

22、 and generally controllers are used to reject disturbances and/or implement set point changes.Changes in feed water temperature constitute a disturbance to the shower process.In theory,a controller can be used to control any process which has a measurable output(PV),a known ideal value for that outp

23、ut(SP)and an input to the process(MV)that will affect the relevant PV.Controllers are used in industry to regulate temperature,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

24、utilizes automated control.Due to 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.2.PID controller theory Note:This section describes the ideal parallel or non-interacting fo

25、rm of the PID controller.For other forms please see the Section Alternative notation and PID forms.The PID control scheme is named after its three correcting terms,whose sum constitutes the manipulated variable(MV).Hence:where Pout,Iout,and Dout are the contributions to the output from the PID contr

26、oller from each of the three terms,as defined below.2.1.Proportional term The proportional term makes a change to the output that is proportional to the current error value.The proportional response can be adjusted by multiplying the error by a constant Kp,called the proportional gain.The proportion

27、al term is given by:Where Pout:Proportional output Kp:Proportional Gain,a tuning parameter e:Error=SP PV t:Time or instantaneous time(the present)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

28、 is too high,the system 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 too low,the control action may be too small when responding to syst

29、em disturbances.In the absence of disturbances,pure proportional control will not settle at its target value,but will retain a 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

30、it is the proportional term that should contribute the bulk of the output change.2.2.Integral term The contribution from the integral term is proportional to both the magnitude of the error and the duration of the error.Summing the instantaneous error over time(integrating the error)gives the accumu

31、lated offset that should have been corrected previously.The accumulated error is then multiplied by the integral gain and added to the controller output.The magnitude of the contribution of the integral term to the overall control action is determined by the integral gain,Ki.The integral term is giv

32、en by:Iout:Integral output Ki:Integral Gain,a tuning parameter e:Error=SP PV :Time in the past contributing to the integral response The integral term(when added to the proportional term)accelerates the movement of the process towards set point and eliminates the residual steady-state error that occ

33、urs with a proportional only controller.However,since the integral term is responding to accumulated errors from the past,it can cause the present value to overshoot the set point value(cross over the set point and then create a deviation in the other direction).For further notes regarding integral

34、gain tuning and controller stability,see the section on loop tuning.2.3 Derivative term The rate of change of the process error is calculated by determining the slope of the error over time(i.e.its first derivative with respect to time)and multiplying this rate of change by the derivative gain Kd.Th

35、e magnitude of the contribution of the derivative term to the overall control action is termed the derivative gain,Kd.The derivative term is given by:Dout:Derivative output Kd:Derivative Gain,a tuning parameter e:Error=SP PV t:Time or instantaneous time(the present)The derivative term slows the rate

36、 of change of the controller output and this effect is most noticeable close to the 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 sign

37、al 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 and the derivative gain are sufficiently large.2.4 Summary The output from the three terms,the proportional,the integral and the derivative t

38、erms are summed to calculate the output of the PID controller.Defining u(t)as the controller output,the final form of the PID algorithm is:and the tuning parameters are Kp:Proportional Gain-Larger Kp typically means faster response since the larger the error,the larger the Proportional term compensa

39、tion.An excessively large proportional gain will lead to process instability and oscillation.Ki:Integral Gain-Larger Ki implies steady state errors are eliminated quicker.The trade-off is larger overshoot:any negative error integrated during transient response must be integrated away by positive err

40、or before we reach steady state.Kd:Derivative Gain-Larger Kd decreases overshoot,but slows down transient response and may lead to instability due to signal noise amplification in the differentiation of the error.二 Matlab Introduction The MATLAB environment is well suited to rapid prototyping and ap

41、plication development.The interactive programming environment,built-in math functions,toolboxes,editing and debugging tools,and deployment options all contribute to reducing your overall development time.By using the built-in math functions and the many specialized functions contained within our too

42、lboxes,MATLAB can significantly reduce the time it takes you to develop prototypes.In addition to integrated editing and debugging tools,MATLAB provides a performance profiler to help you further optimize your code when programming in MATLAB.Building applications around complex algorithms and graphi

43、cs is easier than ever with the GUI builder,GUIDE.GUIDE was redesigned in MATLAB 6 to save you time.It offers all the drag and drop interface options you would expect,such as text boxes,radio buttons,check boxes,listboxes,sliders,pop-up menus,frames and more.When youre ready to deploy your applicati

44、on,the MathWorks offers a number of different options that allow you to either convert or interface your MATLAB application to other environments including C/C+and the Web.MATLAB is the most productive development environment for creating scientific and engineering applications because it offers pow

45、erful tools for every step in the process to reduce your overall development time.MATLAB is a high-performance language for technical computing.It integrates computation,visualization,and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical no

46、tation.Typical uses include Math and computation Algorithm development Data acquisition Modeling,simulation,and prototyping Data analysis,exploration,and visualization Scientific and engineering graphics Application development,including graphical user interface building 三 DDE Introduction Dynamic d

47、ata exchange(DDE,Dynamic data exchange)is real-time exchange data between applications,it is the effective method between different applications to share data a agreement.DDE agreement is a kind of open,and language unrelated,based on protocol,it allows multiple applications to any human agreed form

48、at data exchange or command.It is application through Shared memory process of the communication between a form,also need not user intervention of good data exchange method.DDE applications can be divided into four types:client and server and client/server and the monitor.Conversation is a basic con

49、cept of DDE.DDE conversation happened in client applications and server application between.Customer is responsible for initializing and attendant session and control conversation flow,from the server application request data or services;The server application response client applications of data or

50、 service request.Client/server applications is both client applications and server application request,it can be and can provide information.Monitor application for debugging purposes.DDE applications can have multiple burst conversation,a service applications can also have multiple client applicati