A fuzzy-neural adaptive control for MIMO nonlinear system with application

被引：0
|
作者：
Piao, YG [1 ]
Yang, ZQ [1 ]
Li, YQ [1 ]
Li, M [1 ]
He, XQ [1 ]
机构：
[1] HiSense Grp, Ctr Technol, Qingdao 266071, Peoples R China
来源：
PROCEEDINGS OF THE 3RD WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-5 | 2000年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the fuzzy identification proposed by Takaki and Sugeno [1] is extended to the MIMO adaptive controller based on a hybrid neural network structure. The network is roughly divided into the premise and consequence corresponding to the T-S model. Each parameter of the consequence function Is convenient to be adjusted by the extended Bp algorithm so that automatic rule modification can be realized. The membership function of each fuzzy subset can be modified by genetic: algorithm (GA). In this way, the more pre-knowledge for plant need not required. Finally, the MIMO fuzzy-neural control is used to simulation of a real example.
引用
收藏
页码：935 / 939
页数：5
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