Observer-based Adaptive Iterative Learning Control for Nonlinear Systems with Time-varying Delays  

作　　者：Wei-Sheng Chen Rui-Hong Li Jing Li 

机构地区：[1]Department of Applied Mathematics, Xidian University, X{an 710071, PRC

出　　处：《International Journal of Automation and computing》2010年第4期438-446,共9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.60804021,No.60702063)

摘　　要：An observer-based adaptive iterative learning control （AILC） scheme is developed for a class of nonlinear systems with unknown time-varying parameters and unknown time-varying delays. The linear matrix inequality （LMI） method is employed to design the nonlinear observer. The designed controller contains a proportional-integral-derivative （PID） feedback term in time domain. The learning law of unknown constant parameter is differential-difference-type, and the learning law of unknown time-varying parameter is difference-type. It is assumed that the unknown delay-dependent uncertainty is nonlinearly parameterized. By constructing a Lyapunov-Krasovskii-like composite energy function （CEF）, we prove the boundedness of all closed-loop signals and the convergence of tracking error. A simulation example is provided to illustrate the effectiveness of the control algorithm proposed in this paper.An observer-based adaptive iterative learning control （AILC） scheme is developed for a class of nonlinear systems with unknown time-varying parameters and unknown time-varying delays. The linear matrix inequality （LMI） method is employed to design the nonlinear observer. The designed controller contains a proportional-integral-derivative （PID） feedback term in time domain. The learning law of unknown constant parameter is differential-difference-type, and the learning law of unknown time-varying parameter is difference-type. It is assumed that the unknown delay-dependent uncertainty is nonlinearly parameterized. By constructing a Lyapunov-Krasovskii-like composite energy function （CEF）, we prove the boundedness of all closed-loop signals and the convergence of tracking error. A simulation example is provided to illustrate the effectiveness of the control algorithm proposed in this paper.

关 键 词：Adaptive iterative learning control （AILC） nonlinearly parameterized systems time-varying delays Lyapunov- Krasovskii-like composite energy function. 

分 类 号：TP271[自动化与计算机技术—检测技术与自动化装置] TP273.22[自动化与计算机技术—控制科学与工程]