Decentralized output feedback adaptive NN tracking control of interconnected nonlinear time-delay systems with prescribed performance

被引:19
|
作者
Hua, Chuangchun [1 ]
Wang, Yuanyuan [1 ]
Li, Yafeng [1 ]
Li, Huiguang [1 ]
机构
[1] Yanshan Univ, Inst Elect Engn, Qinhuangdao 066004, Peoples R China
基金
国家教育部博士点专项基金资助; 中国国家自然科学基金;
关键词
Neural network control; Time-delay; Prescribed performance control (PPC); Decentralized filters; DYNAMIC SURFACE CONTROL; DEAD-ZONE INPUT; STABILIZATION;
D O I
10.1016/j.neucom.2015.09.104
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 studies the decentralized output feedback adaptive NN tracking control problem for interconnected nonlinear time-delay systems with prescribed performance. By using the novel states transformation, the prescribed tracking performance can be guaranteed. Firstly, we design the decentralized filters independent of time delay to estimate the unmeasured state variables. By estimating the bounds of the unknown parameters instead of themselves, it can avoid the over-estimation problem. Then, by using RBF (radial basis function) neural network (NN) to approximate the unavailable time-delay functions, we construct the adaptive neural network output feedback controller with corresponding adaptive laws. It is proved that all the signals of the overall closed-loop systems are ultimately uniformly bounded. Finally, simulation examples are presented to verify the effectiveness of the theoretic results obtained. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:885 / 896
页数:12
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