Switching set-point control of nonlinear system based on RBF neural network

被引：0
|
作者：
Li, Xiao-Li [1 ]
机构：
[1] Univ Sci & Technol Beijing, Informat & Engn Sch, Dept Automat, Beijing 100083, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 1, PROCEEDINGS | 2007年 / 4491卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Multiple controllers based on multiple radial based function neural network(RBFNN) models are used to control a nonlinear system to trace a set-point. Considering the nonlinearity of the system, when the set-point value is time variant, a controller based on a fixed structure RBFNN can not give a good control performance. A switching controller which switches among different controller based on different RBFNN is used to adapt the varing set-point value and improve the output reponse and control performance of the nonlinear system.
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页码：87 / 92
页数：6
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