Adaptive fuzzy neural control of nonlinear systems

被引：0
|
作者：
Gao, Y [1 ]
Er, MJ [1 ]
Deng, C [1 ]
机构：
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Instrumentat & Syst Engn Lab, Singapore 639798, Singapore
来源：
COMPUTATIONAL INTELLIGENT SYSTEMS FOR APPLIED RESEARCH | 2002年
关键词：
D O I：
10.1142/9789812777102_0056
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a robust Adaptive Fuzzy Neural Controller (AFNC) suitable for identification and control of uncertain Multi-Input-Multi-Output (MIMO) non-linear systems. The proposed controller has the following salient features: (1) Self-organizing fuzzy neural structure, (2) Fast online learning ability; (3) Adaptive robust control. Simulation studies on a two-link robot manipulator show that the performance of the proposed controller is excellent.
引用
收藏
页码：461 / 468
页数：8
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