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Sensorless Control of Synchronous Reluctance Motor Drives Based on the TLS EXIN Neuron

Authors :
Siwan Narayan
Abdoul N'Diaye
Giansalvo Cirrincione
Salah Laghrouche
Maurizio Cirrincione
Yong-Chao Liu
Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST)
Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC)
Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS)
University of the South Pacific (USP)
Source :
International Electric Machines & Drives Conference, International Electric Machines & Drives Conference, May 2019, San Diego, CA, United States
Publication Year :
2019
Publisher :
HAL CCSD, 2019.

Abstract

International audience; This paper proposes a rotor speed and position estimation scheme for the synchronous reluctance motor (SynRM) drive system based on its active flux model in the stator reference frame and the total least squares (TLS) EXIN neuron. Firstly, the active flux model of the SynRM in the stator reference frame is reconstructed to the overdetermined matrix equations. On the basis of that, the estimation of the rotor speed of the SynRM is transferred into solving a TLS problem. The TLS EXIN neuron, which is a recursive TLS algorithm, is used to solve this problem online to extract the rotor speed. The estimated rotor position is obtained from the estimated rotor speed based on the integrator. The feasibility and effectiveness of the proposed rotor speed estimation scheme have been verified by the simulation results.

Details

Language :
English
Database :
OpenAIRE
Journal :
International Electric Machines & Drives Conference, International Electric Machines & Drives Conference, May 2019, San Diego, CA, United States
Accession number :
edsair.doi.dedup.....ad08de99672be75d295e4c7184440f7f