Dual Motor Model Prediction Control with Senseless Control and Parameter Identification Function

Abstract

A new control strategy is proposed to address the issues of poor stability and inability to achieve torque synchronization in dual-drive systems. Firstly, the structure of the permanent magnet assisted synchronous reluctance motor is described, and the principles of model prediction dual-torque control, Beetle Antennae Search algorithm, and Kalman filter algorithm are analyzed. The permanent magnet assisted synchronous reluctance motor is used as the main motor, and a senseless control module and parameter identification module for the motor is established on this basis, creating a model prediction dual-torque control model for the dual motor with the above functions. Finally, through simulation, the rationality and accuracy of the model are verified. The results show that the model can balance the torque of the two motors and achieve accurate senseless control and parameter identification.