Strong Track Schmidt Filter and Its Application to Speed Sensorless Control of Induction Motor
强跟踪延迟滤波算法及其在感应电机无速度传感器控制中的应用

Based on strong track filter(STF)and Schmidt extended Kalman filter (SEKF),a strong track Schmidt filter (STSF)is proposed.By using the reduced-order model of induction motor,a state estimation algorithm is established and is applied to speed sensorless control system of induction motor.Comparison has been made between the extended Kalman filter(EKF),SEKF,and STF algorithms in terms of motor state estimation performance.Simulation and experiment results show that STSF is better than EKF on the estimating accuracy,tracking speed,restraining noise,and moreover, its computational complexity is also largely decreased.It is proved that STSF algorithm can carry out the task of motor speed and flux estimations in real time.