Research On Model Predictive Control Of The Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor plays a leading role increasingly in practical applications because of its own high power factor, good safety performance and low energy consumption. Therefore, the study of the permanent magnet motor becomes a hot topic in the field of motor.Model Predictive Control (MPC) has gotten a high-performance control results in the field of process control and has achieved successfully considering the affection of the future state of the system to control the amount. In addition, the model predictive control can solve the impact of constraints on system performance effectively, and ensure that the system has the ideal steady-state and dynamic performance. In this paper, based on the mathematical model of permanent magnet synchronous motor and vector control thought, motor speed and current dual-closed-loop cascade model predictive controller is designed, outer speed loop is the output and inner cross-axis current is the reference signal.In addition, due to the problem of motor torque ripple caused by imprecise and external measurement error of the stator structure itself have a serious impact on the motor, and caused great difficulty to control precisely. Based on periodic pulsation characteristics, and the principle of iterative learning control, a method of compensation is proposed, and based on the original cascade model predictive controller and the increase of cross-axis reference current compensation link to suppress the torque ripple, simulation results show that the proposed method to compensate the current can reduce torque ripple of the motor effectively.