Please use this identifier to cite or link to this item: http://hdl.handle.net/10198/2213
Title: A new approach for speed estimation in induction motor drives based on a reduced-order extended Kalman filter
Author: Leite, V.
Araújo, R.
Freitas, D.
Keywords: Kalman filters
Covariance matrices
Induction motor drives
Machine control
Nonlinear filters
Nonlinear filters
Nonlinear filters
Robust control
Rotors
Issue Date: 2004
Publisher: IEEE
Citation: Leite, V.; Araújo, R.; Freitas, D. (2004) - A new approach for speed estimation in induction motor drives based on a reduced-order extended Kalman filter. In IEEE International Symposium on Industrial Electronics. Ajaccio, Córcega.
Abstract: This paper presents and proposes a new approach to achieve robust speed estimation in induction motor sensorless control. The estimation method is based on a reduced-order extended Kalman filter (EKF), instead of a full-order EKF. The EKF algorithm uses a reduced-order state-space model structure that is discretized in a particular and innovative way proposed in this paper. With this model structure, only the rotor flux components are estimated, besides the rotor speed itself. Important practical aspects and new improvements are introduced that enable us to reduce the execution time of the algorithm without difficulties related to the tuning of covariance matrices, since the number of elements to be adjusted is reduced.
URI: http://hdl.handle.net/10198/2213
Appears in Collections:DE - Publicações em Proceedings Indexadas ao ISI/Scopus

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