Adaptive friction compensation for industrial robot control

We deal with the friction compensation in the model-based trajectory tracking control of an industrial robot manipulator. First it is shown that the variations of the friction term might significantly affect the control performances during the robot operations. Then, a simple adaptive scheme is proposed to solve the problem, allowing us to keep the trajectory tracking errors at a constant low level. Experimental results, obtained in a typical industrial environment, show the effectiveness of the method and how it is comparable with known neural-network-based techniques