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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Martin Kuchar
VSB–Technical University of Ostrava
Computer Science & IT

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Comparison of the speedy estimate methods of the induction motors Thinh Cong Tran; Pavel Brandstetter; Hau Huu Vo; Chau Si Thien Dong; Martin Kuchar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 1: February 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i1.24089

Abstract

This paper deals with a novel method to achieve the effective performance of the extended Kalman filter (EKF) for the speedy estimate of an induction motor. The real coding genetic algorithm (GA) is used to optimize the components of the covariance matrix in the EKF, thus ensuring the stability and accuracy of the filter in the speed estimation. The advantage of the proposed method is less dependent on the parameters of the induction motor. The content includes the vector control model for induction motor, the speed estimation by modeling the reference frame-model reference adaptive system (RF-MRAS), the current based-model reference adaptive system (CB-MRAS), and the speed estimation with the EKF optimized by genetic algorithm. Simulative studies on the field-oriented controller (FOC) with different operating conditions are performed in Matlab Simulink when the rotor resistance changes in the current speed estimation methods. The simulation results demonstrate the efficiency of the proposed GA-EKF filter compared with other speed estimation methods of induction motors. 
Co-Authors Chau Si Thien Dong Hau Huu Vo Pavel Brandstetter Thinh Cong Tran