文献类型：期刊文献

英文题名：Razumikhin-Nussbaum-lemma-based adaptive neural control for uncertain stochastic pure-feedback nonlinear systems with time-varying delays

作者：Yu, Zhaoxu[1];Li, Shugang[2];Du, Hongbin[1]

机构：[1]E China Univ Sci & Technol, Dept Automat, Shanghai 200237, Peoples R China;[2]Shanghai Jiao Tong Univ, Dept Ind Engn & Logist, Shanghai 200240, Peoples R China

年份：2013

卷号：23

期号：11

起止页码：1214

外文期刊名：INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL

收录：;EI(收录号：20132616447848);WOS:【SCI-EXPANDED(收录号:WOS:000320398700003)】；

基金：The authors would like to thank the editors and reviewers for their kind help and comments. The work was supported in part by Natural Science Foundation of China under grant numbers 60704013 and 60974066, the Natural Science Foundation of Shanghai under grant number 11ZR1409800, and the Special Foundation of East China University of Science and Technology for Youth Teacher under grant number YH0157134.

语种：英文

外文关键词：stochastic nonlinear system; adaptive control; neural network; Razumikhin-Nussbaum lemma; time-varying delay

摘要：This paper addresses the problem of adaptive neural control for a class of uncertain stochastic pure-feedback nonlinear systems with time-varying delays. Major technical difficulties for this class of systems lie in: (1) the unknown control direction embedded in the unknown control gain function; and (2) the unknown system functions with unknown time-varying delays. Based on a novel combination of the Razumikhin-Nussbaum lemma, the backstepping technique and the NN parameterization, an adaptive neural control scheme, which contains only one adaptive parameter is presented for this class of systems. All closed-loop signals are shown to be 4-Moment semi-globally uniformly ultimately bounded in a compact set, and the tracking error converges to a small neighborhood of the origin. Finally, two simulation examples are given to demonstrate the effectiveness of the proposed control schemes. Copyright (c) 2012 John Wiley & Sons, Ltd.