Enhanced Speed Control of PMSM Using an Optimized SRUKF Algorithm

Abstract

An improved square root unscented Kalman filter (SRUKF) algorithm is proposed to reduce the motor speed error in the presence of interference. In the simulation experiment, interference is added to affect the motor operation. The d − qmotor speed value is predicted using information such as the motor's shaft current, electrical angular velocity and rotor position. The improved algorithm is used to control the speed to reduce the error caused by the interference on the motor speed, and the algorithm is compared with the traditional unscented Kalman filter algorithm. The results show that the algorithm has less system computation, and the error of the motor speed with interference controlled by the algorithm is smaller than the true value without interference, and it has better robustness.