To improve the position tracking accuracy of permanent magnet synchronous linear motor, a variable universe fuzzy iterative learning control strategy with adaptive forgetting factor is proposed and applied to the motor control system. The control strategy integrates the advantages of fuzzy logic, iterative learning and adaptive forgetting factor, which can effectively improve the tracking accuracy of the control system. Variable universe fuzzy controller dynamically changes the size of the universe by scaling factor, and a two-level fuzzy controller is designed to generate scaling factor. Adaptive forgetting factor is used to reduce the position error during iterative learning cycle switching. Smooth switching strategy and slow stepping strategy are designed to improve the adaptive rate of forgetting factor and further reduce the position error during cyclic switching. The results show that this control method can effectively improve the position tracking accuracy and accelerate the convergence speed.