Speed estimation for permanent magnet synchronous motor based on robust extended Kalman filter
基于抗差扩展卡尔曼滤波器的永磁同步电机转速估计策略

By analyzing the impact of gross error on the estimation accuracy of extended Kalman filter (EKF), we propose a novel speed estimation method for the permanent magnet synchronous motor (PMSM) in sensorless vector control based on Robust extended Kalman filter (REKF). The model of permanent magnet synchronous motor based on REKF is developed. We investigate whether REKF can give better estimation performance than EKF when PMSM is disturbed by gross errors. The speed estimation error of REKF caused by external gross error and internal estimation gross error is compared with that of EKF. Simulation and experimental results show that REKF provides better performance and exhibit faster convergence than EKF under disturbances.