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Parameter identification of squirrel cage induction machine using linear Kalman filter

Author(s)
Mokhlis Salah-Eddine Department of Physics, GITIL Laboratory, Faculty of Sciences Ain Chock Hassan II University, Casablanca, Morocco
Sadki Said Department of Physics, GITIL Laboratory, Faculty of Sciences Ain Chock Hassan II University, Casablanca, Morocco
Barra Adil Department of Physics, GITIL Laboratory, Faculty of Sciences Ain Chock Hassan II University, Casablanca, Morocco
Bensassi Bahloul Department of Physics, GITIL Laboratory, Faculty of Sciences Ain Chock Hassan II University, Casablanca, Morocco
Abstract
In the industrial environment, the induction machine is generally the most used, given its low cost, its efficiency, and its reliability. To obtain optimal operation, it is essential to collect values of its parameters (stator and rotor resistances and inductions). This data can be used to prevent breakdowns and ensure these machines' rational use. In this context, this article proposes a new method to estimate the internal parameters of these machines using the KALMAN FILTER. Simulations under the MATLAB environment have been developed. Their results show that the estimated parameters are close to the nominal ones.
Publication Details
Page(s) 861-867
DOI DOI not available
Published Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 18, Issue: 7, Year: 2023

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Keywords
squirrel cage induction machine, recursive least square, Kalman Filter, system identification
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