Title :
Joint stick-slip friction compensation for robotic manipulators by iterative learning
Author_Institution :
Inst. of Inf. Sci., Acad. Sinica, Nankang, Taiwan
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
Keywords :
compensation; dynamics; force control; friction; intelligent control; iterative methods; learning (artificial intelligence); manipulators; tracking; two-term control; PD control; dynamics; iterative learning control; joint stick-slip friction compensation; robotic manipulators; trajectory tracking; Feedback control; Force control; Friction; Lubrication; Manipulator dynamics; Motion control; Robot motion; Steady-state; Tracking; Trajectory;
Conference_Titel :
Intelligent Robots and Systems '94. 'Advanced Robotic Systems and the Real World', IROS '94. Proceedings of the IEEE/RSJ/GI International Conference on
Conference_Location :
Munich
Print_ISBN :
0-7803-1933-8
DOI :
10.1109/IROS.1994.407431
