Adaptive Tracking Control of Uncertain MIMO Nonlinear Systems with Time-varying Delays and Unmodeled Dynamics  

作　　者：Xiao-Cheng Shi Tian-Ping Zhang 

机构地区：[1]Department of Automation, College of Information Engineering, Yangzhou University

出　　处：《International Journal of Automation and computing》2013年第3期194-201,共8页国际自动化与计算杂志（英文版）

基　　金：supported by National Natural Science Foundation of China(No.61174046)

摘　　要：In this paper, adaptive neural tracking control is proposed based on radial basis function neural networks （RBFNNs） for a class of muki-input multi-output （MIMO） nonlinear systems with completely unknown control directions, unknown dynamic disturbances, unmodeled dynamics, and uncertainties with time-varying delay. Using the Nussbaum function properties, the unknown control directions are dealt with. By constructing appropriate Lyapunov-Krasovskii functionals, the unknown upper bound functions of the time-varying delay uncertainties are compensated. The proposed control scheme does not need to calculate the integral of the delayed state functions. Using Young＇s inequality and RBFNNs, the assumption of unmodeled dynamics is relaxed. By theoretical analysis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded.In this paper, adaptive neural tracking control is proposed based on radial basis function neural networks （RBFNNs） for a class of muki-input multi-output （MIMO） nonlinear systems with completely unknown control directions, unknown dynamic disturbances, unmodeled dynamics, and uncertainties with time-varying delay. Using the Nussbaum function properties, the unknown control directions are dealt with. By constructing appropriate Lyapunov-Krasovskii functionals, the unknown upper bound functions of the time-varying delay uncertainties are compensated. The proposed control scheme does not need to calculate the integral of the delayed state functions. Using Young＇s inequality and RBFNNs, the assumption of unmodeled dynamics is relaxed. By theoretical analysis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded.

关 键 词：Adaptive control unmodeled dynamics time-varying delays neural networks Nussbaum function 

分 类 号：TN919.3[电子电信—通信与信息系统] TP13[电子电信—信息与通信工程]