A learning variable structure controller of a flexible one-link manipulator

Abstract

In this paper, tip regulation of a flexible one-link manipulator by Learning Variable Structure Control (LVSC) is investigated. Sliding surface is designed according to a selected reference model which relocates system poles to be negative real ones, hence link vibration is eliminated. The proposed LVSC incorporates a learning mechanism to improve regulation accuracy. Rigorous proof shows: the state's tracking error sequence converges uniformly to zero; the uniformly bounded learning control sequence converges to the equivalent control almost everywhere. A more detailed journal version of this paper is presented in [1].