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|Title:||A comparative study of Kalman filtering for sensorless control of a permanent-magnet synchronous motor drive|
|Source:||IEMDC 2005 : 2005 IEEE International Conference on Electric Machines and Drives : May 15, 2005, San Antonio, Tex., p. 815-822 How to cite?|
|Abstract:||This paper presents a comparative study of the novel Unscented Kalman Filter (UKF) and the Extended Kalman Filter (EKF) for estimation of the rotor speed and position of a permanent-magnet synchronous motor (PMSM) drive. The general structure of the EKF and the UKF are reviewed. The various system vectors, matrices, models and algorithm programs are presented. Simulation studies on the two Kalman filters are carried out using Matlab and Simulink to explore the usability of the UKF in a sensorless PMSM drive. In order to compare the estimation performances of the observers, both filters are designed for the same motor model and control system and run with the same covariances. The simulation results indicate that the UKF is capable of tracking the actual rotor speed and position provided that the elements of the covariance matrices are properly selected. Since covariance tuning of the Kalman filter is often a trial-and-error process, an unconventional, asymmetric way of setting the model covariance parameters is introduced. It is shown that tuning is easier and the method gives a significant improvement in performance and filter stability.|
|Rights:||© 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
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|Appears in Collections:||Conference Paper|
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