文献类型：期刊文献

英文题名：ADAPTIVE NEURAL DYNAMIC SURFACE CONTROL FOR NONLINEAR PURE-FEEDBACK SYSTEMS WITH MULTIPLE TIME-VARYING DELAYS: A LYAPUNOV-RAZUMIKHIN METHOD

作者：Yu, Zhao-Xu[1];Yu, Zhao-Sheng[2]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]S China Univ Technol, Sch Elect Power, Guangzhou 510640, Guangdong, Peoples R China

年份：2013

卷号：15

期号：4

起止页码：1124

外文期刊名：ASIAN JOURNAL OF CONTROL

收录：;EI(收录号：20132916504323);WOS:【SCI-EXPANDED(收录号:WOS:000329204400016)】；

基金：This work was partly supported by National Natural Science Foundation of China under grant 60974066, Natural Science Foundation of Shanghai under grant 12ZR1408200 and grant 11ZR1409800.

语种：英文

外文关键词：Nonlinear system; adaptive neural control; dynamic surface control; time-delay; Razumikhin functional

摘要：This paper focuses on the problem of adaptive neural control for a class of uncertain nonlinear pure-feedback systems with multiple unknown time-varying delays. The considered problem is challenging due to the non-affine pure-feedback form and the unknown system functions with multiple unknown time-varying delays. Based on a novel combination of mean value theorem, Razumikhin functional method, dynamic surface control (DSC) technique and neural network (NN) parameterization, a new adaptive neural controller which contains only one parameter is developed for such systems. Moreover, The DSC technique can overcome the problem of explosion of complexity' in the traditional backstepping design procedure. All closed-loop signals are shown to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. Two simulation examples are given to verify the effectiveness of the proposed design.