Joint stick-slip friction compensation for robotic manipulators by iterative learning

Abstract

This paper studies the compensation of internal joint stick-slip friction effects for desired trajectory tracking of robotic manipulators. A PD type iterative learning control, which incorporates a stabilizing feedback control for robot dynamics, is applied to compensate for the friction. Simulations of a two-link robotic manipulator show that our friction compensation scheme is effective for different friction models whose characteristics are not exactly known a priori.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>