文献类型：期刊文献

英文题名：Neural-network-based output-feedback adaptive dynamic surface control for a class of stochastic nonlinear time-delay systems with unknown control directions

作者：Yu, Zhaoxu[1];Li, Shugang[2]

机构：[1]E China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]Shanghai Jiao Tong Univ, Dept Ind Engn & Logist, Shanghai 200240, Peoples R China

年份：2014

卷号：129

起止页码：540

外文期刊名：NEUROCOMPUTING

收录：;EI(收录号：20140717320621);WOS:【SCI-EXPANDED(收录号:WOS:000332132400058)】；

语种：英文

外文关键词：Stochastic time-delay systems; Output-feedback; Neural network; Dynamic surface control; Unknown control direction

摘要：This paper focuses on the problem of output-feedback adaptive stabilization for a class of stochastic nonlinear time-delay systems with unknown control directions. First, based on a linear state transformation, the unknown control coefficients are lumped together and the original system is transformed to a new system for which control design becomes feasible. Then, after the introduction of an observer, an adaptive neural network (NN) output-feedback control scheme is presented for such systems by using dynamic surface control (DSC) technique and Lyapunov-Krasovskii method. The designed controller ensures that all the signals in the closed-loop system are 4-Moment (or 2-Moment) semi-globally uniformly ultimately bounded. Finally, a numerical example is given to demonstrate the feasibility and effectiveness of the proposed control design. (C) 2013 Elsevier B.V. All rights reserved.