Adaptive neural network tracking design for a class of uncertain nonlinear discrete-time systems with dead-zone

被引：0
|
作者：
LIU YanJun [1 ]
LIU Lei [1 ]
TONG ShaoCheng [1 ]
机构：
[1] College of Science,Liaoning University of Technology
来源：
ScienceChina(InformationSciences) | 2014年 / 57卷 / 03期
基金：
中国国家自然科学基金;
关键词：
adaptive control; RBF neural network; non-symmetric dead-zone; backstepping design; uncertain nonlinear systems;
D O I：
暂无
中图分类号：
O231 [控制论（控制论的数学理论）];
学科分类号：
摘要：
In this paper,the stability and control issues of a class of uncertain nonlinear discrete-time systems in the strict feedback form are investigated.The dead-zone input in the systems,whose property is non-symmetric and discretized,is investigated.The unknown functions in the systems are approximated by using the radial basis function neural networks(RBFNNs).Backstepping design procedure is employed in the controller and the adaptation laws design.Lyapunov analysis method is utilized to prove the stability of the closed-loop system.A simulation example is given to illustrate the efectiveness of the proposed approach.
引用
收藏
页码：276 / 287
页数：12
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