Design and Implementation of an Extended Kalman Filter for the State Estimation of a Permanent Magnet Synchronous Motor

Rached Dhaouadi, Ned Mohan, Lars Norum

Research output: Contribution to journalArticlepeer-review

332 Scopus citations

Abstract

Practical considerations for implementing the discrete extended Kalman filter in real time with a digital signal processor are discussed. The system considered is a permanent magnet synchronous motor (PMSM) without a position sensor, and the extended Kalman filter is designed for the online estimation of the speed and rotor position by only using measurements of the motor voltages and currents. The algorithms developed to allow efficient computation of the filter are presented. The computational techniques used to simplify the filter equations and their implementation in fixed-point arithmetic are discussed. Simulation and experimental results using the TMS 320C25 digital signal processor are presented to demonstrate the feasibility of this estimation process.

Original languageEnglish (US)
Pages (from-to)491-497
Number of pages7
JournalIEEE Transactions on Power Electronics
Volume6
Issue number3
DOIs
StatePublished - Jul 1991

Bibliographical note

Funding Information:
The authors wish to thank Texas Instruments Inc. for providing the TMS320C25 development tools. The financial support of this project by the University of Minnesota Center for Electric Energy is gratefully acknowledged.

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