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

作     者：LIU YanJun LIU Lei TONG ShaoCheng 

作者机构：College of ScienceLiaoning University of Technology 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2014年第57卷第3期

页      面：276-287页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 071101[理学-系统理论] 0811[工学-控制科学与工程] 0701[理学-数学] 

基　　金：supported in part by National Natural Science Foundation of China(Grant Nos.61074014,61104017) Program for Liaoning Innovative Research Team in University(Grant No.LT2012013) Program for Liaoning Excellent Talents in University(Grant No.LJQ2011064) 

主　　题：adaptive control RBF neural network non-symmetric dead-zone backstepping design uncertain nonlinear systems 

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 *** dead-zone input in the systems,whose property is non-symmetric and discretized,is *** 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 *** 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.