Neural networks robust adaptive control for a class of MIMO uncertain nonlinear systems

被引：0
|
作者：
Hu, TL [1 ]
Zhu, JH [1 ]
Hu, CH [1 ]
Sun, ZQ [1 ]
机构：
[1] Tsing Hua Univ, Dept Comp Sci & Technol, State Key Lab Intelligent & Syst, Beijing 100084, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS | 2005年 / 3498卷
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：
This paper presents a robust adaptive control scheme for a class of multi-input multi-output (MIMO) uncertain nonlinear systems. Multiple multilayer neural networks are used to compensate for the model uncertainty. The on-line updating rules of the neural networks parameters are obtained by Lyapunov stability theory. All signals in the closed-loop system are bounded. The output tracking error converges to a small neighborhood of zero, while the stability of the closed-loop system is guaranteed. Finally the effectiveness of the control scheme is verified by a simulation of two-link manipulator.
引用
收藏
页码：60 / 68
页数：9
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