A Position Estimator Using Kalman Filter with a Data Rejection Filter for a Long-Stator Linear Synchronous Motor of Maglev

Abstract

As a maglev levitates with a small air gap and runs very fast, securing the levitation system's stability is crucial. Thus, the high-performance decoupling control between the propulsion control system and the levitation system is of critical importance. The study described in this paper focuses on a high-performance position estimator that minimizes the dynamic coupling between the levitation system and propulsion system in a maglev's propulsion control system using a long-stator linear synchronous motor. To that end, a position estimator using a Kalman filter was designed. Then the stability of the designed filter and its characteristics and problems that result from the change in the measurement covariance value were identified through a stability analysis of the Kalman filter. Moreover, in an attempt to improve it, a Kalman filter with a data rejection filter was proposed. Afterward, to verify the performance of the proposed position estimator, a maglev train model was fabricated and for each Kalman filter measurement covariance value, the dynamic coupling between the propulsion control system and the levitation system was identified through the test. For the Kalman filter using a data rejection filter, it was confirmed that the propulsion control system could minimize the influence on the levitation system when an inaccurate position of the vehicle is renewed.