本科毕业设计 智能PID控制及其在温控系统中的应用.docx

本科毕业设计 智能PID控制及其在温控系统中的应用.docx

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本科毕业设计智能PID控制及其在温控系统中的应用

本科毕业论文

题目：

智能PID控制及其在温控系统中的应用姓

名：

郑俊达学院：

信息科学与技术学院

系：

电子工程系

专

业：

电子信息工程年

级：

2005级学号：

22220051204132

指导教师（校内）：

杨涛职称：

教授

指导教师（校外）：

无

职称：

2009年5月28日

智能PID控制器及其在原油井筒加热电源温度控制中的应用仿真研究

摘要本文主要研究PID控制器的控制原理，模糊PID和动词PID控制器作为智能PID控制器，各有其特点。

选择原油井筒加热电源作为控制对象，用Matlab仿真工具Simulink以及Matlab程序语言对各种PID控制进行仿真，对仿真结果进行比较分析。

关键词PID控制器

模糊PID控制计算动词PID控制

温度控制系统Simulink仿真

Matlab程序语言仿真I

IntelligentPIDcontrollersandresearchontheSimulationoftheirapplicationstothe

temperaturecontrolofoilcanisterheater

AbstractThisarticlefocusesonPIDcontroller,fuzzyPIDcontrollerandcomputationalverbPIDcontrolleraretwodifferentkindsofintelligentPIDcontrollers,bothofthemshowsomecharacteristics.Inthispaper,thecontrolplantwaschosenasanoilcanister,ofwhichthetemperaturewascontrolled.SimulationswereperformedbasedontwodifferentkindsofPIDcontrollers,byusingMatlabtoolSimulink,andMatlabprogramlanguage.ThesimulationresultsofdifferentkindsofPIDcontrollerswerecompared.

KeyWordsPIDcontroller,fuzzyPIDcontrol,computationalverbPIDcontrol,temperature-control-system,SimulinkSimulation,Matlabprogramlanguage

II

摘要······································································································I

Abstract·······································································································

II引言······································································································VI

1PID控制器··································································································1

1.1PID控制器的概念[1]··············································································1

1.1.1PID控制原理··············································································1

1.1.2PID三个环节的作用·····································································1

1.2PID控制器的种类················································································2

1.2.1传统PID控制器···········································································2

1.2.2智能PID控制器···········································································2

2模糊PID控制器····························································································3

2.1模糊控制规则[1]···················································································3

2.1.1控制原理···················································································3

2.1.2模糊规则···················································································3

2.2模糊控制规则的实现············································································4

2.2.1隶属度[1]···················································································4

2.2.2模糊推理[2]················································································5

2.3在Matlab中建立模糊判决器···································································6

2.3.1用FISEditor建立模糊判决器[3]·······················································6

2.3.2用Matlab程序生成模糊判决器[1]·····················································7

2.3.3模糊判决器的使用·······································································

93动词PID控制器····························································································10

3.1动词控制规则·····················································································10

3.1.1模糊规则的动词化·······································································10

3.1.2动词规则[4]················································································10

3.2动词相似度························································································11

3.2.1基于进化函数的动词相似度的计算[4]···············································11

3.2.2简化的动词相似度[5]····································································12

III

厦门大学本科毕业设计（论文

3.3动词控制规则的实现[4]··········································································144用Simulink进行PID控制仿真··········································································15

4.1采油油管加热电源简介[6]·······································································15

4.1.1背景·························································································15

4.1.2系统函数···················································································15

4.2Simulink简介[3]····················································································15

4.3传统PID控制Simulink仿真·····································································15

4.3.1建立系统模型·············································································15

4.3.2调试过程及结果··········································································16

4.4模糊PID控制Simulink仿真·····································································17

4.4.1建立系统模型·············································································17

4.4.2调试·························································································18

4.5关于动词PID控制Simulink仿真的一点说明················································18

4.6本章小结···························································································195用Matlab编写程序进行各种PID控制仿真···························································20

5.1仿真程序流程图··················································································20

5.2关键环节的算法··················································································21

5.2.1ode45求解微分方程[7]··································································21

5.2.2对延时的近似处理·······································································21

5.3传统PID控制仿真················································································22

5.3.1调整过程及结果··········································································22

5.3.2关于两种不同仿真方法的说明························································22

5.4模糊PID控制仿真················································································23

5.4.1模糊推理源代码分析····································································23

5.4.2参数调整及仿真结果····································································24

5.5动词PID控制仿真················································································25

5.5.1基于进化函数求相似度的动词PID控制的仿真调试······························25

5.5.2基于简化的动词相似度的控制仿真调试············································27

5.6小结·································································································29结

论······································································································30致谢······································································································31

IV

参考文献····································································································32

引言

PID控制器以其结构简单、稳定性好、工作可靠、调整方便等优点被广泛应用于工业控制系统，但现代工业控制系统越来越复杂，被控对象往往表现出时滞、非线性、时变性，控制要求越来越高，传统的PID控制器难以满足现代工业控制的需求，智能型PID控制器呈现出广阔的发展空间。

模糊PID控制器是模糊控制器和PID控制器的有效结合，它兼具模糊控制和PID控制的优点；动词PID控制器是在模糊PID控制器的基础上实现了控制规则“动词化”，对模糊PID控制进行了一些改进。

目前动词PID控制器用于实际的工业控制系统还不多，本文的研究也仅处于软件仿真阶段。

1PID

控制器

图1.1:

PID控制器

1.1PID控制器的概念[1]

1.1.1PID控制原理

PID控制器是一种线性闭环控制器，它根据给定输入值rin（t与实际输出值yout（t构成控制偏差

error（t=rin（t−yout（t

（1.1PID的控制信号u（t由errot（t及其对时间的积分、微分三部分联合作用产生：

u（t=kp（error（t+1T1t0errot（tdt+TDderrot（tdt=kp（error（t+kit0errot（tdt+kdderrot（tdt（1.2

PID控制器最终理想的控制效果是errot（t=0，即yout（t=rin（t。

将控制器写成传递函数的形式：

G（s=U（sE（s=kp（1+1TIs+TDs=kp+ki1s+kds（1.3

式中，kp――比例系数，TI――积分时间常数，TD――微分时间常数；统一用比例系数表示，ki为积分比例系数，kd为微分比例系数：

ki=

kpTI,kd=kpTD（1.4

1.1.2PID三个环节的作用

比例、微分、积分各个环节的作用：

（1kp：

减小系统的误差，加快系统的响应速度。

（2ki：

消除系统的静态误差，决定积分作用的强弱。

（3kd：

抵制偏差信号的变化趋势，对偏差进行提前预报，减少调节时间。

1.2PID控制器的种类

PID控制器有传统PID控制器、模糊PID控制器、专家PID控制器、以及动词PID控制器等几类。

1.2.1传统PID控制器

PID控制器的参数整定是控制系统设计的核心。

图1.1中的PID控制器表示的就是传统的PID控制器，其kp、ki、kd三个参数在控制过程中不会自动发生变化，操作人员只能根据控制对象的特性在系统开始工作时选择最优的三个参数。

但仅靠一组参数还不能满足系统的要求，在控制过程中一般还要手动对参数进行修改，由此造成了极大的不方便。

工业中实际应用的PID控制器不会只用传统的PID控制策略。

1.2.2智能PID控制器

模糊PID控制器、专家PID控制器、以及动词PID控制器都是智能PID控制器，它们在传统PID控制器的基础上实现了很多改进。

模糊PID控制器和动词PID控制器都是PID参数自整定型控制器；而专家PID根据专家经验库，可能调整PID参数，或者直接影响输出电压u。

本文主要对模糊PID控制器和动词PID控制器进行研究比较，详细介绍见后面的章节。

2模糊PID控制器

模糊PID控制器全称应该叫做“模糊参数自适应（自整定）PID控制器”。

图2.1表示其系统组成。

顾名思义，模糊PID控制器的三个参数是能够在线调整、实时改变的。

这是模糊PID控制器在传统PID

控制器的基础上实现的重大改进。

图2.1:

模糊PID控制器

2.1模糊控制规则[1]

2.1.1控制原理

自适应控制应用现代控制理论，以对象特性为基础，在线辨识对象特征参数，实时改变控制策略。

在控制过程中各种信号量不易定量表示，因此需要模糊理论来解决问题。

自适应模糊PID控制器以误差e和误差变化ec作为输入，找到输出的三个PID参数与e和ec之间的模糊关系。

在运行中不断检测e和ec，利用模糊控制规则在线对PID参数进行修改，以满足不同e和ec对控制参数的不同要求，而使被控对象有良好的动、静态性能。

2.1.2模糊规则

误差e、误差变化率ec，以及∆K的模糊子集均为{NB,NM,NS,ZO,PS,PM,PB}，分别代表{负大、负中、负小、零、正小、正中、正大}。

模糊控制规则具有如下形式：

If（eisNBand（ecisNBthen（kpisPBand（kiisNBand（kdisPS。

由于e和ec都有7个子集元素，总共有49种自由组合，因此模糊控制总共有49条这样形式的规则。

kp、ki、kd三个参数整定的模糊控制规则表如表2.1。

kp的模糊规则表

ec

∆KpNBNMNSZOPSPMPBNBZOZONMNMNMNBNBNMPSZONSNMNMNMNBNSPSPSZONSNSNMNMe

ZOPMPMPSZONSNMNMPSPMPMPMPSZONSNSPMPBPB

PM

PS

PS

ZONSPB

PB

PBPMPMPSZO

ZO

k的模糊规则表

ec∆KiNBNMNSZOPSPMPBNBNBNBNMNMNSZOZONMNBNBNMNSNSZOZONSNBNMNSNSZOPSPSe

ZONMNMNSZOPSPMPMPSNMNSZOPSPSPMPBPMZOZO

PS

PS

PM

PBPBPB

ZO

ZOPSPMPMPB

PB

kd的模糊规则表

ec∆KdNBNMNSZOPSPMPBNBPBPMPMPMPSPSPBNMPBNSPSPSPSPSPBNSZOZOZOZOZOZOZOe

ZOZONSNSNSNSNSZOPSZONSNMNMNSNSZOPMPSNSNBNMNMNSZOPB

PS

NS

NB

NB

NB

NM

PS

表2.1:

模糊控制规则表

2.2模糊控制规则的实现

2.2.1

隶属度[1]

在模糊控制规则表中，各个元素子集都是用字母表示的，而在控制过程中，模糊判决器的输入和输出都是一些数值，因此需要在数值和各个语言变量之间建立联系。

各个语言变量都表示一定的范围，这种范围的覆盖面可以用隶属度来表示。

隶属度函数有多种形状，有正态分布的，有等腰梯形的，最常用的是三角形，如图2.2所示。

每个语言变量表示的范围可能有所交叉，但除了几个特殊点，一个具体数值隶属于各个字母符号的程度是不一样的。

图2.2:

隶属度

模糊合成推理根据隶属度和模糊控制规则来修正PID参数：

kp=k

p+{ei,eci}pki=ki+{ei,eci}ikd=kd+{e