Abstract: UsingextendedKalmanfilter (EKF) to estimate the position of permanent magnet linear synchronous motor(PMLSM), the model is not accurate, the noise properties areuncertain,and may lead to the problem of filtering divergence.Adouble forgetting Kalman filter (DFKF) method was proposed. Adaptive fading factor on the basisof EKF was introduced to achieve the first forgetting,andthe Sage-Husa adaptive filter algorithm was introduced to realize the second forgetting. The experiments show that DFKF diminishesaccording to the law of sineregardless synchronous speed change or load mutation;the stable error is 0.469% or 0.943% before or after the load mutation; the final error stabilizes near 0.167%;the effects will be better with the longer time of the simulation.

Key words: PMLSM, Kalmanfilter, adaptive fading factor, Sage-Husa adaptive filter, DFKF