Tuning convergence rate of a robust learning controller for robot manipulators

Abstract

This paper presents a robust learning control algorithm which learns the entire span of robot trajectory within a finite time interval. The learning controller treats the uncertain parameters as well as unknown external disturbances with the aid of the linear parameterization property of the robot system and robust feedback control input. It is shown that the robot motion converges exponentially to the desired one as the iteration continues.