A Novel Speed Estimation Algorithm for a Permanent Magnet Linear Synchronous Motor Using Extended Kalman Filter with Multiple Fading Factors

A Suboptimal Multiple Fading Extended Kalman Filter (SMFEKF) for the permanent magnet linear synchronous motor (PMLSM) is proposed to achieve accurate speed estimation and high reliability of the PMLSM sensorless drive system, which is under parameter mismatch and sudden load disturbance. Firstly, the dynamic mathematical model of the PMLSM is established. Secondly, an Extended Kalman Filter (EKF) is designed to estimate the speed and position of the PMLSM, and a SMFEKF is introduced to improve the estimation performance of the proposed algorithm under the parameter mismatch and sudden change of load conditions. Finally, the EKF and SMFEKF-based PMLSM systems are simulated and experimentally compared. The results show that the proposed algorithm can realize the accurate estimation of the speed and position of PMLSM under different conditions, and it is verified that the introduction of multiple fading factors can improve the estimation effect of the algorithm significantly.