Iterative learning control of linear induction motor based on model-free adaptive control

As a special type of motors, linear induction motors have been an important area of research for researchers. But the linear induction motor poses a great challenge for velocity control due to its nonlinearity, strong coupling and unique end effects. In this paper, a model-free adaptive control method is used to simplify the model by using the load disturbance as the input signal firstly. Secondly, the model-free adaptive control method is combined with the iterative learning control method to design a reasonable controller for the problem of low control accuracy, and the stability of the control system is proved by Lyapunov method. Finally, simulation results show that the velocity tracking effect is further enhanced after the addition of iterative learning control, which verifies the accuracy and effectiveness of the composite method.