Composite iterative learning controller design for gradually varying references with applications in an AFM system
来源期刊：中南大学学报(英文版)2014年第1期
论文作者：FANG Yong-chun(方勇纯) ZHANG Yu-dong(张玉东) DONG Xiao-kun(董晓坤)
文章页码：180 - 189
Key words：iterative learning control; saturation; feedback control; feedforward control; atomic force microscope
Abstract: 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 control 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.
FANG Yong-chun(方勇纯), ZHANG Yu-dong(张玉东), DONG Xiao-kun(董晓坤)
(Institute of Robotics and Automatic Information System, Nankai University, Tianjin 300071, China)
Abstract: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 control 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.
Key words:iterative learning control; saturation; feedback control; feedforward control; atomic force microscope
