文献类型：期刊文献

英文题名：Observer-based adaptive neural dynamic surface control for a class of non-strict-feedback stochastic nonlinear systems

作者：Yu, Zhaoxu[1];Li, Shugang[2];Li, Fangfei[3]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Dept Automat, Shanghai 200237, Peoples R China;[2]Shanghai Univ, Sch Management, Dept Informat Management, Shanghai, Peoples R China;[3]E China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China

年份：2016

卷号：47

期号：1

起止页码：194

外文期刊名：INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE

收录：;EI(收录号：20152000855695);WOS:【SCI-EXPANDED(收录号:WOS:000360556300014)】；

基金：This work was partially supported by the Natural Science Foundation of P.R. China [grant number 61304071], [grant number 71271132], [grant number 61403139]; the Natural Science Foundation of Shanghai [grant number 12ZR1408200]; the Science and Technology Commission of Shanghai Municipality [grant number 14YF1404500]; the Fundamental Research Funds for the Central Universities and the CSC scholarship.

语种：英文

外文关键词：stochastic nonlinear systems; neural network; variable separation; dynamic surface control; output feedback

摘要：The problem of adaptive output feedback stabilisation is addressed for a more general class of non-strict-feedback stochastic nonlinear systems in this paper. The neural network (NN) approximation and the variable separation technique are utilised to deal with the unknown subsystem functions with the whole states. Based on the design of a simple input-driven observer, an adaptive NN output feedback controller which contains only one parameter to be updated is developed for such systems by using the dynamic surface control method. The proposed control scheme ensures that all signals in the closed-loop systems are bounded in probability and the error signals remain semi-globally uniformly ultimately bounded in fourth moment (or mean square). Two simulation examples are given to illustrate the effectiveness of the proposed control design.