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

页码：461 / 468

页数：8

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