文献类型：期刊文献

英文题名：Sliding-mode control for nonlinear state-delayed systems using neural-network approximation

作者：Niu, Y.[1]; Lam, J.[2]; Wang, X.[1]; Ho, D.W.C.[3]

机构：[1]E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]Univ Hong Kong, Dept Engn Mech, Hong Kong, Hong Kong, Peoples R China;[3]City Univ Hong Kong, Dept Math, Hong Kong, Hong Kong, Peoples R China

年份：2003

卷号：150

期号：3

起止页码：233

外文期刊名：IEE PROCEEDINGS-CONTROL THEORY AND APPLICATIONS

收录：;EI(收录号：2003287536951);WOS:【SCI-EXPANDED(收录号:WOS:000183698800004)】；

语种：英文

外文关键词：Approximation theory - Asymptotic stability - Computer simulation - Control nonlinearities - Lyapunov methods - Matrix algebra - Neural networks - Nonlinear control systems - Theorem proving

摘要：The sliding-mode control problem is studied for a class of state-delayed systems with mismatched parameter uncertainties, unknown nonlinearities and external disturbances. By integrating neural-network approximation and the Lyapunov theory into the sliding-mode technique, a neural-network-based sliding-mode control scheme is proposed. The major advantage of the present work over traditional sliding-mode designs is the relaxation of the requirement that the unknown nonlinearities are to be bounded. By means of linear matrix inequalities, a sufficient condition for ensuring the asymptotic stability of the sliding-mode dynamics restricted to the defined sliding surface is given. Further, by utilising a neural-network model to approximate the unknown nonlinearity, a sliding-mode control scheme is proposed to guarantee that the system state trajectory is attracted to the designed sliding surface.