Dual-Mode Friction Compensation of a Precision Linear-Motor Rolling-Guide Stage

摘要

In this article, characterization and compensation for the friction in a linear-motor rolling-guide stage are reported. The friction was characterized by a fuzzy-set-based model and self-learning genetic algorithm. Because the system dynamics of the micro and macro modes are very different, a two-stage fuzzy PID controller is proposed to determine the optimal servo gains for both modes. The fuzzy PID controller possesses a switching mechanism that continuously tunes the servo gains according to the motion stage states. From the simulation and experiment, the proposed controller shows good tracking and positioning accuracy after friction compensation.