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.
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.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2012年第8期1090-1093,共4页
Control Theory & Applications
基金
国家自然科学基金资助项目(61074054)
关键词
边界层
迭代学习控制
自适应控制
滑模变结构控制
boundary layer
iterative learning control
adaptive control
sliding mode variable structure control
