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International Journal of Electrical and Computer Engineering (IJECE)
Article . 2021 . Peer-reviewed
License: CC BY SA
Data sources: Crossref
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Article . 2021
License: CC BY
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Parameters estimation of BLDC motor based on physical approach and weighted recursive least square algorithm

Authors: Rania Majdoubi; Lhoussaine Masmoudi; Mohammed Bakhti; Abderrahmane Elharif; Bouazza Jabri;

Parameters estimation of BLDC motor based on physical approach and weighted recursive least square algorithm

Abstract

Brushless DC motors (BLDCM) are widely used when high precision converters are required. Model based torque control schemes rely on a precise representation of their dynamics, which in turn expect reliable system parameters estimation. In this paper, we propose two procedures for BLDCM parameters identification used in an agriculture mobile robot’s wheel. The first one is based on the physical approach or equations using experimentation data to find the electrical and mechanical parameters of the BLDCM. The parameters are then used to elaborate the model of the motor established in Park’s reference frame. The second procedure is an online identification based on recursive least square algorithm. The procedure is implemented in a closed-loop scheme to guarantee the stability of the system, and it provide parameter matrices obtained by transforming electrical equations, established in Parks reference frame, and mechanical equation to discrete-time domain. From these matrices, and using well formulated intermediate variables, all desired parameters are deduced simultaneously. The identification procedures are being verified using simulation under Matlab-Simulink software.

Keywords

Park's reference frame, Weighted recursive least square, Brushless DC motors, Physical approach, Online identification, Parameters identification

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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