Control performance of discrete-time fuzzy systems improved by neural networks

被引：0
|
作者：
Su, Chien-Hsing [1 ]
Huang, Cheng-Sea
Lian, Kuang-Yow
机构：
[1] Natl Taiwan Univ Sci & Technol, Dept Elect Engn, Taipei 10673, Taiwan
[2] Chung Yuan Christian Univ, Dept Elect Engn, Chungli 32023, Taiwan
来源：
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES | 2006年 / E89A卷 / 05期
关键词：
T-S fuzzy systems; fuzzy modeling; discrete-time systems; neural networks; linear matrix inequalities;
D O I：
10.1093/ietfec/e89-a.5.1446
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new control scheme is proposed to improve the system performance for discrete-time fuzzy systems by tuning control grade functions using neural networks. According to a systematic method of constructing the exact Takagi-Sugeno (T-S) fuzzy model, the system uncertainty is considered to affect the membership functions. Then, the grade functions, resulting from the membership functions of the control rules, are tuned by a back-propagation network. On the other hand, the feedback gains of the control rules are determined by solving a set of LMIs which satisfy sufficient conditions of the closed-loop stability. As a result, both stability guarantee and better performance are concluded. The scheme applied to a truck-trailer system is verified by satisfactory simulation results.
引用
收藏
页码：1446 / 1453
页数：8
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