Adaptive fuzzy friction compensation for linear motor servo systems

Due to the influence of friction, the linear motor with contact surface frequently appears rough running and control precision deterioration during low speed operation. To overcome this problem, an adaptive friction compensation method was proposed. Through tuning the parameters of a fuzzy model adaptively, the friction model was estimated. Then the friction was compensated according to its estimate, consequently the influence of friction could be eliminated. This method used composite adaptation, which utilized the relative information of output tracking error and parameter estimation error simultaneously, to accelerate the parameter convergence. By using composite adaptation, the parameters of the fuzzy model could converge to the optimal values under certain conditions. In this paper, the close loop stability and parameter estimate convergence for the proposed method were proved. Simulation demonstrates that the proposed method can realize good online friction estimation and compensation, hence the control performance of the linear motor is improved.