A multivariable generalized predictive control approach based on T-S fuzzy model

被引：0
|
作者：
Zhang, HG [1 ]
Cai, LL
Bien, Z
机构：
[1] Northeastern Univ, Dept Automat Control, Shenyang 110006, Peoples R China
[2] Hong Kong Univ Sci & Technol, Dept Mech Engn, Kowloon, Hong Kong, Peoples R China
[3] Korea Adv Inst Sci & Technol, Dept Elect Engn, Yusong Ku, Taejon 305701, South Korea
来源：
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2000年 / 9卷 / 3-4期
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：
In this paper, the Takagi-Sugeno (T-S) fuzzy model is used to express dynamic systems, and an on-line identification algorithm for its parameters and structures is presented. A new multivariable fuzzy generalized predictive control approach is put forward based on the identified fuzzy model by means of Clark's principle of single-variable generalized predictive control, some of whose performances are analysed in detail. A simulation study of the multivariable load system of electric generating unit shows that the approach is superior to conventional load control systems.
引用
收藏
页码：169 / 189
页数：21
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