Please use this identifier to cite or link to this item: http://hdl.handle.net/10198/2218
Title: A new online identification methodology for flux and parameters estimation of vector controlled induction motors
Author: Leite, V.
Araújo, R.
Freitas, D.
Keywords: Kalman filters
Induction motors
Machine vector control
Magnetic flux
Magnetic flux
Matrix algebra
Rotors
State-space methods
Statistical analysis
Stators Magnetic flux
Issue Date: 2003
Publisher: IEEE
Citation: Leite, V.; Araújo, R.; Freitas, D. (2003) - A new online identification methodology for flux and parameters estimation of vector controlled induction motors. In IEEE International Electric Machines and Drives Conference. Madison, USA. p. 449-455. ISBN 0-7803-7817-2
Abstract: A new online identification methodology for estimation of the rotor flux components and the main electrical parameters of vector controlled induction motors is presented in this paper. The induction motor model is referred to the rotor reference frame for estimation of rotor flux and rotor parameters, and referred to the stator reference frame to estimate stator parameters. The stator parameters estimation is achieved by a prediction error method based on a model structure described by a linear regression that is independent of rotor speed and rotor parameters. The rotor flux components and rotor parameters are estimated by a reduced order extended Kalman filter, using a 4th-order state-space model structure where the state equation is described by matrices that are diagonal and independent of rotor speed as well as stator parameters. Both methods work in a boot-strap manner.
URI: http://hdl.handle.net/10198/2218
ISBN: 0-7803-7817-2
Publisher Version: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1211302&tag=1
Appears in Collections:DE - Publicações em Proceedings Indexadas ao ISI/Scopus

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