文献类型：期刊文献

英文题名：Adaptive neural control for uncertain stochastic nonlinear strict-feedback systems with time-varying delays: A Razumikhin functional method

作者：Yu, Zhaoxu[1];Du, Hongbin[1]

机构：[1]E China Univ Sci & Technol, Dept Automat, Shanghai 200237, Peoples R China

年份：2011

卷号：74

期号：12-13

起止页码：2072

外文期刊名：NEUROCOMPUTING

收录：;EI(收录号：20112114000144);WOS:【SCI-EXPANDED(收录号:WOS:000291915500004)】；

基金：The authors would like to thank the editors and reviewers for their kind help and comments. The work was supported by Natural Science Foundation of P.R. China (60704013) and Shanghai Leading Academic Discipline Project (B504).

语种：英文

外文关键词：Stochastic nonlinear systems; Adaptive control; Neural network (NN); Razumikhin functional; Time-varying delays

摘要：This paper addresses the problem of adaptive neural control for a class of uncertain stochastic nonlinear strict-feedback systems with time-varying delays. A novel adaptive neural control scheme is presented for this class of systems, based on a combination of the Razumikhin functional approach, the backstepping technique and the neural network (NN) parameterization. The proposed adaptive controller guarantee that all the error variables are 4-Moment semi-globally uniformly ultimately bounded in a compact set while the system output converges to a small neighborhood of the reference signal. Two simulation examples are given to demonstrate the effectiveness of the proposed control schemes. (C) 2011 Elsevier B.V. All rights reserved.