PID参数整定技术的研究及应用

Research and Application on the PID Parameters Tuning Technology

作者: 专业:机械电子工程 导师:刘德平 年度:2010  院校: 郑州大学

Keywords

PID controller, Parameters tuning, Auto-tuning, Simulation, Support vector machines
        PID控制是使用最为广泛的一种控制方式,它具有结构简单、鲁棒性强、可靠性高、易于操作等优点。然而在工业生产过程中往往具有非线性、时变不确定性等,难以建立精确的数学模型,传统PID参数整定已不能满足精确控制的要求。本文研究了传统PID控制参数整定与自整定的方法和应用,对目前研究较为成熟的智能PID控制进行了MATLAB环境下的仿真分析和比较,归纳得出了各种控制器的应用场合和优缺点。在传统PID参数整定的基础上,引入新的思想方法和数学工具,深入研究了一种基于最小二乘支持向量机的参数整定PID控制器,在求取控制系统的支持向量机模型的基础上获取最优的三个PID参数,并通过仿真实验验证了该方法的优越性。论文的主要研究内容概括如下:(1)研究常规PID控制及传统算法的优缺点和应用场合,运用MATLAB软件中的simulink仿真工具对本课题所关心的PID控制及相应控制算法进行了仿真分析,验证特征参数的优化和自整定过程,为后来课题的研究做理论铺垫。(2)将最小二乘支持向量机(LS-SVM)与PID参数整定进行有机结合,得到最优化的三个特征参数。利用最小二乘支持向量机良好的非线性函数逼近能力和原理,通过支持向量机求取系统的瞬态数学模型,并在此基础上获取PID控制器三个特征参数值。在MATLAB中进行仿真实验,结果表明该方法对于系统跟踪参考输入、减少由未知干扰引起的系统输出变化的控制是有效的,具有一定的实用性,为PID参数整定研究提供一种新的思路。(3)运用本文提到的新方法,把PID整定应用在玻璃纤维网格布生产线,根据被控对象特性的变化,实时修改PID参数,实现PID最优控制。将其和常规PID控制算法进行仿真比较,通过对被控对象的设定值跟踪性能和抗干扰特性的分析研究,验证基于支持向量机算法下PID调节的优越性。
    PID controller is the most widely control method in the field of industrial process control, and it has the advantage of simple structure, strong robustness, high reliability, easy operation and so on. However, Industrial production processes are often very complicated, and it is difficult to establish accurate mathematical model of the system, therefore the traditional PID controller cannot meet the precise control requirements. This paper firstly discusses the traditional PID controller methods and other usual-used intelligence control algorithm, and then studies the PID parameters tuning, auto-tuning and optimizing with different algorithms. The applications, advantages and disadvantages of PID controllers are described, and the result is validated by MATLAB simulation.This paper in-depth studies one kind of PID controller with parameter tuning which is based on least squares support vector machine, and uses least squares to obtain the optimal parameters of the PID controller. The superiority of this method is verified through the simulation experiments by MATLAB.The main contents and achievements of this dissertation are as follows: The traditional PID controllers and their classical algorithms are studied, and the principles and characteristics of the PID controllers that the topic interested also are explained in detail, which in preparation for the later studies and researches in the theoretical groundwork.Use MATLAB as a data processing tools, through the simulink software analysis and simulates several kinds of PID control systems; the optimization and auto-tuning process for the three parameters of PID controller are verified by MATLAB.A novel algorithm for PID parameter tuning and auto-tuning based on Least-squares Support Vector Machines is put forward. The system’s mathematical model is identified with support vector machines for non-linear system, and the optimal parameters of PID controller are obtained using least squares method. The experimental results show that the method for the system to track the reference input and to reduce the interference caused by unknown changes in system is effective. It is practical and feasible in industrial control. This paper provides a new way of thinking for the study of PID parameter tuning and auto-tuning.Using the new method mentioned in this paper, the PID controller with parameters tuning is applied in glass fiber mesh production line. The parameters of the PID controller are modified in real-time to achieve optimal control effect. Compared with the conventional PID controller, the simulation result demonstrates that this method which is based on support vector machine algorithm is superior to the conventional methods.
        

PID参数整定技术的研究及应用

摘要4-5
Abstract5-6
目录7-10
1 绪论10-18
    1.1 课题研究的意义10-11
    1.2 PID控制应用及研究现状11-14
        1.2.1 PID控制技术的应用及特点11-13
        1.2.2 PID控制技术的研究现状13-14
    1.3 支持向量机的研究现状14-16
    1.4 本文研究的内容16-18
2 PID参数整定与自整定18-39
    2.1 引言18
    2.2 PID参数整定概述18-28
        2.2.1 Ziegler-Nichols整定法19-24
        2.2.2 临界比例度法24-25
        2.2.3 衰减曲线法25-27
        2.2.4 试凑法27-28
        2.2.5 理论整定法28
    2.3 PID参数自整定概述28-37
        2.3.1 基于模型的PID参数自整定29-30
        2.3.2 基于规则的PID参数自整定30-33
        2.3.3 智能PID参数自整定33-37
            2.3.3.1 基于蚁群算法的PID控制器33-35
            2.3.3.2 基于神经网络的PID控制器35-36
            2.3.3.3 基于支持向量机的PID控制器36-37
    2.4 本章小结37-39
3 支持向量机在PID参数整定中的应用39-52
    3.1 引言39
    3.2 SVM的原理及其应用39-47
        3.2.1 支持向量分类机39-43
        3.2.2 支持向量回归机43-45
        3.2.3 最小二乘支持向量机45-47
    3.3 基于支持向量机的PID参数整定控制器47-50
        3.3.1 基于最小二乘支持向量机的PID参数整定48-50
        3.3.2 改变惩罚系数μ改善整定特性50
    3.4 仿真实验50-51
    3.5 本章小结51-52
4 PID控制器在玻璃纤维生产线中的应用52-59
    4.1 引言52
    4.2 生产工艺简介52-53
    4.3 方案分析53-54
    4.4 控制系统结构设计54
    4.5 被控系统的数学建模54-56
    4.6 仿真分析56-58
    4.7 本章小结58-59
5 总结与展望59-61
    5.1 总结59-60
    5.2 展望60-61
参考文献61-65
致谢65-66
在学期间发表的学术论文与研究成果66
        下载全文需68


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