文献类型：期刊文献

英文题名：Adaptive neural output feedback control for stochastic nonlinear time-delay systems with input and output quantization

作者：Yang, Yekai[1];Yu, Zhaoxu[1];Li, Shugang[2];Sun, Jitao[3]

机构：[1]East China Univ Sci & Technol, Dept Automat, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Shanghai Univ, Dept Informat Management, Shanghai 200444, Peoples R China;[3]Univ Johannesburg, Inst Intelligent Syst, Johannesburg, South Africa

年份：2018

卷号：282

起止页码：146

外文期刊名：NEUROCOMPUTING

收录：;EI(收录号：20180104598894);WOS:【SCI-EXPANDED(收录号:WOS:000424893200015)】；

基金：The authors would like to appreciate the editors and reviewers for their valuable comments and kind help. This work is partially supported by the Chinese National Natural Science Foundation under grant nos. 71271132 and 61673296, Shanghai Pujiang Program under grant no. 15PJC049, and Fundamental Research Funds for the Central Universities under grant nos. 222201714055 and 222201717006.

语种：英文

外文关键词：Stochastic nonlinear systems; Quantization; Output feedback; Time delay; Neural network

摘要：The problem of output feedback adaptive tracking control is studied for a class of stochastic nonlinear time-delay systems in which the measured output and input signals are quantized by two sector-bounded quantizers respectively. An observer including the quantized input and output signals is designed to estimate the unknown system states, and the unknown system functions with less restrictions are dealt with by using the neural network's (NN) approximation. By combining the backstepping technique and the Lyapunov-Krasovskii method, an observer-based adaptive neural quantized tracking control scheme is presented for this class of systems. The stability analysis indicates that the tracking error can converge to a small neighborhood of the origin while all closed-loop signals are 4-moment (or 2-moment) semi-globally uniformly ultimately bounded (SGUUB). Finally, two illustrative examples are provided to demonstrate the feasibility and effectiveness of the proposed design methodology. (C) 2017 Elsevier B.V. All rights reserved.