首页 | 本学科首页   官方微博 | 高级检索  
     

基于C-R模糊模型的广义预测控制算法
引用本文:翟春艳,李书臣. 基于C-R模糊模型的广义预测控制算法[J]. 计算机仿真, 2004, 21(11): 80-81
作者姓名:翟春艳  李书臣
作者单位:辽宁石油化工大学信息学院自动化系,辽宁,抚顺,113001;辽宁石油化工大学信息学院自动化系,辽宁,抚顺,113001
摘    要:该文对非线性系统的建模采用Cao-Ress(C-R)模糊模型,并用卡尔曼滤波算法在线辨识模糊模型的结论参数,从而减少了参数辨识的数量和避免了矩阵的求逆运算,然后在每一个采样点对该系统进行局部动态线性化,根据得到的系统线性化模型对系统采取广义预测控制(GPC)方法得到当前的控制动作。仿真结果表明了该方法的有效性。

关 键 词:模糊模型  广义预测控制  非线性系统  卡尔曼滤波算法
文章编号:1006-9348(2004)11-0080-02
修稿时间:2003-05-13

Algorithm of Generalized Predictive Control Based on C-R Fuzzy Model
ZHAI Chun-yan,LI Shu-chen. Algorithm of Generalized Predictive Control Based on C-R Fuzzy Model[J]. Computer Simulation, 2004, 21(11): 80-81
Authors:ZHAI Chun-yan  LI Shu-chen
Abstract:A Cao-Ress(C-R) fuzzy model is constructed for nonlinear system, and the consequence parameters identification is obtained on-line by using Kalman filtering algorithm, so the number of parameters' identification is reduced and the calculation of matrix inversion is avoided. Local dynamic linearization is applied to the system at each sampling point. Then control action is gained using generalized predictive control(GPC) based on the linearized model. Its effectiveness for nonlinear systems is verified via simulation study.
Keywords:Fuzzy model  Generalized predictive control  Nonlinear system  Kalman filtering algorithm
本文献已被 CNKI 维普 万方数据 等数据库收录!
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