首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于改进型RBF神经网络多变量系统的PID控制
引用本文:李绍铭,刘寅虎.基于改进型RBF神经网络多变量系统的PID控制[J].重庆大学学报(自然科学版),2007,30(2):53-57.
作者姓名:李绍铭  刘寅虎
作者单位:安徽工业大学电气信息学院安徽省电力电子与电力传动重点实验室,马鞍山243002
基金项目:安徽省教育厅自然科学基金
摘    要:针对工业控制中多输入多输出非线性时变系统,提出了基于改进型RBF神经网络的智能PID控制方法.采用最近邻聚类算法在线构造RBF神经网络辨识器并在线辨识被控对象,对PID控制器参数进行在线调整,实现了多变量非线性时变系统的解耦控制.仿真结果表明,控制器能根据系统运行状态获得对应于某种最优控制规律下的PID参数,解耦后的系统具有较好的动态和静态性能,与常规RBF神经网络PID控制方法相比,该方法具有控制精度高、响应速度快的优点,并且具备较强的自适应性和鲁棒性.

关 键 词:改进型RBF神经网络  非线性时变系统  PID控制  最近邻聚类算法  解耦控制
文章编号:1000-582X(2007)02-0053-05
修稿时间:2006-10-21

PID Control for Multivariable System Based on Ameliorative RBF Neural Networks
LI Shao-ming,LIU Ying-hu.PID Control for Multivariable System Based on Ameliorative RBF Neural Networks[J].Journal of Chongqing University(Natural Science Edition),2007,30(2):53-57.
Authors:LI Shao-ming  LIU Ying-hu
Abstract:Aiming at systems which are of characteristics of multi-input and multi-output, nonlinearity and time-variation in the industrial control fields, this paper presents a intelligent PID control method based on ameliorative RBF neural networks, which constructs RBF neural networks identifier on-line and identifies a controlled object on-line by means of adopting the nearest neighbor-clustering algorithm, and adjusts parameters of PID controller on-line and realizes decoupiing control of multivariable, nonlinear and time-variation system. The simulation result indicates that the controller can get parameters which are optimal under some control law, it makes the decoupled system, compared to the PID control method based on the conventional RBF neural networks, has perfect dynamic and static performances, possesses the advantages of high precision, quick response speed and is of great adaptability and robustness.
Keywords:ameliorative RBF neural networks  nonlinear and time-variation system  PID control  nearest neighbor-clustering algorithm  decoupling control
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《重庆大学学报(自然科学版)》浏览原始摘要信息
点击此处可从《重庆大学学报(自然科学版)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号