Adaptive neural control for uncertain systems subject to actuator failure

被引：4
|
作者：
Jia, Tinggang [1 ,2 ]
Zou, Yuanyuan [1 ]
Niu, Yugang [1 ]
机构：
[1] E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China
[2] Shanghai Elect Grp Co Ltd, Shanghai, Peoples R China
来源：
NEUROCOMPUTING | 2011年 / 74卷 / 18期
基金：
中国国家自然科学基金;
关键词：
Adaptive control; Neural network; Actuator failure; Unknown nonlinear function; FAULT-TOLERANT CONTROL; NONLINEAR-SYSTEMS; TIME-DELAYS; NETWORKS; STABILIZATION; DISCRETE;
D O I：
10.1016/j.neucom.2011.06.030
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the design of controller based on neural network is investigated for a class of uncertain systems subject to actuator failures. An adaptive neural controller is designed by utilizing the approximation technique of neural network. The key feature in this work is to remove the requirement on the boundedness of unknown nonlinear functions that is usually encountered in the existing works. Moreover, sufficient conditions are derived such that the closed-loop system is robustly stable. Finally, numerical simulation results are given. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码：3753 / 3759
页数：7
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