A hybrid approach to adaptive fuzzy control based on genetic algorithms

被引：1
|
作者：
Cupertino, F [1 ]
Giordano, V [1 ]
Naso, D [1 ]
Turchiano, B [1 ]
机构：
[1] Politecn Bari, Dipartimento Elettrotecn & Elettr, Bari, Italy
来源：
2004 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOLS 1-7 | 2004年
关键词：
adaptive fuzzy control; genetic algorithm; electric drives;
D O I：
10.1109/ICSMC.2004.1400902
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper considers a hybrid approach to the design of adaptive fuzzy controllers in which two different learning algorithms are combined together to achieve an improved global design strategy. Namely, a GA is devised to optimize all the configuration parameters of the fuzzy controller, including the number Of membership functions and rules, while a Lyapunov-based adaptation law is used to perform a fast and fine tuning of the output singletons of the controller. A hardware non-linear benchmark is used to emphasize the particular effectiveness of the proposed approach in attacking experimental problems.
引用
收藏
页码：3607 / 3612
页数：6
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