Robust iterative learning control for nonlinear systems with measurement disturbances

作     者：Xuhui BuI FashanYu Zhongsheng Hou Haizhu Yang 

作者机构：School of Electrical Engineering & Automation Henan Polytechnic University Jiaozuo 454003 E R. China Henan Provincial Open Laboratory for Control Engineering Key Discipline Henan Polytechnic University Jiaozuo 454003 P. R. China Advanced Control Systems Laboratory Beijing Jiaotong University Beijing 100044 P. R. China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2012年第23卷第6期

页      面：906-913页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 080201[工学-机械制造及其自动化] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：supported by the National Natural Science Foundation of China (61203065 60834001) the Program of Open Laboratory Foundation of Control Engineering Key Discipline of Henan Provincial High Education (KG 2011-10) 

主　　题：iterative learning control (ILC) nonlinear system mea-surement disturbance iteration-varying disturbance. 

摘      要：The iterative learning control （ILC） has been demon-strated to be capable of considerably improving the tracking perfor-mance of systems which are affected by the iteration-independent disturbance. However, the achievable performance is greatly degraded when iteration-dependent, stochastic disturbances are pre-sented. This paper considers the robustness of the ILC algorithm for the nonlinear system in presence of stochastic measurement disturbances. The robust convergence of the P-type ILC algorithm is firstly addressed, and then an improved ILC algorithm with a decreasing gain is proposed. Theoretical analyses show that the proposed algorithm can guarantee that the tracking error of the nonlinear system tends to zero in presence of measurement dis-turbances. The analysis is also supported by a numerical example.