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基于边界层的不确定机器人自适应迭代学习控制
引用本文:何熊熊,秦贞华,张端.基于边界层的不确定机器人自适应迭代学习控制[J].控制理论与应用,2012,29(8):1090-1093.
作者姓名:何熊熊  秦贞华  张端
作者单位:浙江工业大学信息工程学院,浙江杭州,310023
基金项目:国家自然科学基金资助项目(61074054).
摘    要:针对不确定的多连杆机械手的跟踪控制问题,提出一种基于边界层的自适应迭代学习控制方法.自适应控制用来估计系统的未知参数的上界,本文主要特征是基于边界层设计自适应迭代学习控制器,避免了传统方法设计控制器的不连续性,削弱抖振现象的同时也提高系统的鲁棒性.理论证明系统所有信号有界,系统误差渐进收敛到边界层邻域内.仿真表明了算法的有效性.

关 键 词:边界层  迭代学习控制  自适应控制  滑模变结构控制
收稿时间:2012/5/14 0:00:00
修稿时间:7/1/2012 12:00:00 AM

Adaptive iterative learning control for uncertain robot based on boundary layer
HE Xiong-xiong,QIN Zhen-hua and ZHANG Duan.Adaptive iterative learning control for uncertain robot based on boundary layer[J].Control Theory & Applications,2012,29(8):1090-1093.
Authors:HE Xiong-xiong  QIN Zhen-hua and ZHANG Duan
Institution:School of Information Engineering, Zhejiang University of Technology,School of Information Engineering, Zhejiang University of Technology,School of Information Engineering, Zhejiang University of Technology
Abstract:An adaptive iterative learning control algorithm based on boundary layer is proposed for trajectory tracking of uncertain robot systems. Sliding mode variable structure control is used to improve the robustness to disturbance and perturbation, and boundary layer is used to eliminate the chattering of sliding mode control. In the iterative domain, the unknown parameters are tuned and used as part of the controller. We analyze the stability and convergence of this algorithm by using the Lyapunove-like methodology. The simulation results show that the expected control purpose can be achieved using the proposed algorithm.
Keywords:boundary layer  iterative learning control  adaptive control  sliding mode variable structure control
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