Speed Estimation Method of Linear Motor Extended Kalman Filter Based on Attenuation Memory

Abstract

In allusion to the phenomenon that the extended Kalman filter is easy to diverge in the mover position estimation of permanent magnet synchronous linear motor, a linear motor extended Kalman filter speed estimation method based on attenuation memory is designed. By setting the attenuation factor, α, the extended Kalman filter is introduced to increase the weight of the latest speed data and restrain the divergence of the filter, so as to achieve a better speed tracking effect. In the simulation experiment of the sensorless control of a linear motor, the AMEKF algorithm can significantly improve the speed estimation accuracy of standard EKF, and the speed estimation error is reduced by 0.75%. At the same time, it still maintains a good speed tracking effect and good dynamic performance under variable speed and different load conditions.