Composite iterative learning controller design for gradually varying references with applications in an AFM system

作     者：方勇纯 张玉东 董晓坤 FANG Yong-chun;ZHANG Yu-dong;DONG Xiao-kun

作者机构：Institute of Robotics and Automatic Information SystemNankai University 

基　　金：Projects(61127006 61325017)supported by the National Natural Science Foundation of China 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2014年第21卷第1期

页      码：180-189页

摘      要：Learning control for gradually varying references in iteration domain was considered in this research, and a composite iterative learning control strategy was proposed to enable a plant to track unknown iteration-dependent trajectories. Specifically, by decoupling the current reference into the desired trajectory of the last trial and a disturbance signal with small magnitude, the learning and feedback parts were designed respectively to ensure fine tracking performance. After some theoretical analysis, the judging condition on whether the composite iterative learning control approach achieves better control results than pure feedback contro! was obtained for varying references. The convergence property of the closed-loop system was rigorously studied and the saturation problem was also addressed in the controller. The designed composite iterative learning control strategy is successfully employed in an atomic force microscope system, with both simulation and experimental results clearly demonstrating its superior performance.

主 题 词：iterative learning control saturation feedback control feedforward control atomic force microscope 

学科分类：08[工学] 0803[工学-仪器类] 

核心收录：

D　O　I：10.1007/s11771-014-1929-0

馆 藏 号：203873740...