Torque Ripple Reduction in Brushless DC Motors Based on Model Predictive Control

This paper proposes the application of model predictive control (MPC) to reduce torque ripple for brushless DC motors (BLDCM). The equivalent structure of BLDCM with stator current predictive control is built. In predictive control, the error between the output of BLDCM and predictive model is used to design feedback adjustment and rolling optimization controller. Compared to traditional proportional integral (PI) control, MPC for current closed loop control can improve the controlling precision and robustness of BLDCM. The results of simulation and experiment show that stator current can be improved and torque ripple can be reduced obviously after the use of predictive control.