Adaptive neural control for pure-feedback nonlinear time-delay systems with unknown dead-zone: a Lyapunov-Razumikhin method  

作　　者：Zhaoxu YU Jianxu LUO Ji LIU 

机构地区：[1]Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology

出　　处：《控制理论与应用（英文版）》2013年第1期18-26,共9页

基　　金：supported by the National Natural Science Foundation of China (No. 60974066);the Natural Science Foundation of Shanghai (Nos.12ZR1408200, 11ZR1409800);the Fundamental Research Funds for the Central Universities

摘　　要：This paper addresses the problem of adaptive neural control for a class of uncertain pure-feedback nonlinear systems with multiple unknown state time-varying delays and unknown dead-zone. Based on a novel combination of the Razumikhin functional method, the backstepping technique and the neural network parameterization, an adaptive neural control scheme is developed for such systems. All closed-loop signals are shown to be semiglobally uniformly ultimately bounded, and the tracking error remains in a small neighborhood of the origin. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control schemes.This paper addresses the problem of adaptive neural control for a class of uncertain pure-feedback nonlinear systems with multiple unknown state time-varying delays and unknown dead-zone. Based on a novel combination of the Razumikhin functional method, the backstepping technique and the neural network parameterization, an adaptive neural control scheme is developed for such systems. All closed-loop signals are shown to be semiglobally uniformly ultimately bounded, and the tracking error remains in a small neighborhood of the origin. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control schemes.

关 键 词：Pure-feedback nonlinear systems Adaptive neural control Razumikhin functional TIME-DELAY DEADZONE 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TM343[自动化与计算机技术—控制科学与工程]