Better robot tracking accuracy with phase lead compensated ILC

In this paper, a learning control scheme is proposed to improve robot tracking accuracy. Through the analysis in frequency domain, it is shown that phase lead compensation can broad the learnable frequency band of a learning control system. The phase lead compensation is realized by phase lead filtering the error of last repetition. In theory a filter whose phase difference to the system is within ±90° can be a candidate for the phase lead compensation process. Experimental results on an industrial robot system show that the proposed scheme is both effective and robust against dynamic modeling errors.