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Designing an extended Kalman filter for estimating speed and flux of an induction motor with unknown noise covariance | IEEE Conference Publication | IEEE Xplore

Designing an extended Kalman filter for estimating speed and flux of an induction motor with unknown noise covariance


Abstract:

This paper presents methods of combining the extended Kalman filtering/smoothing, the maximum likelihood (ML) estimation, and expectation maximization (EM) for estimating...Show More

Abstract:

This paper presents methods of combining the extended Kalman filtering/smoothing, the maximum likelihood (ML) estimation, and expectation maximization (EM) for estimating the rotor speed and flux of the induction motor online in the case in which process and measurement noise statistics are not known.
Date of Conference: 15-18 May 2016
Date Added to IEEE Xplore: 03 November 2016
ISBN Information:
Conference Location: Vancouver, BC, Canada

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