Adaptive neural control for a class of output feedback time delay nonlinear systems

被引：40

作者：

Zhu, Qing ^{[1
]}

Zhang, Tianping ^{[1
]}

Fei, Shumin ^{[2
]}

Zhang, Kanjian ^{[2
]}

Li, Tao ^{[2
]}

机构：

[1] Yangzhou Univ, Coll Informat Engn, Yangzhou 225009, Jiangsu, Peoples R China

[2] Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China

来源：

NEUROCOMPUTING | 2009年 / 72卷 / 7-9期

关键词：

Output feedback; Input delay; Backstepping; Neural networks; Adaptive control; BACKSTEPPING CONTROL; NETWORKS; STABILIZATION; STABILITY; DESIGN;

D O I：

10.1016/j.neucom.2008.12.023

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An output feedback control scheme combined with backstepping, radial basis function (RBF) neural networks, and adaptive control is proposed for the stabilization of nonlinear system with input delay and disturbances. A filter and a virtual observer are constructed to substitute the immeasurable system state. By using state transformation, the original system is converted to the system without input delay. Neural networks are employed to estimate the unknown continuous functions. The control scheme ensures that the closed-loop system is semi-globally uniformly ultimately bounded (SGUUB). (c) 2009 Elsevier B.V. All rights reserved.

引用

页码：1985 / 1992

页数：8

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