Dynamic model of Torus motor drive using ANN and FSE methods for the back EMF estimation

A. H. Al-Badi; A. Gastli

doi:10.1080/15325000490228405

Dynamic model of Torus motor drive using ANN and FSE methods for the back EMF estimation

A. H. Al-Badi^*, A. Gastli

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In this article, two dynamic models of the Torus machine are discussed. The first model uses the Fourier series expansion for the back emf and is implemented with PSpice. The second model uses the neural network estimation of the back emf and is implemented with Matlab/Simulink. The models may be used to study the steady-state as well as the transient performances of the machine operating as a motor or as a generator. Experimental results are compared with Matlab/Simulink and PSpice predictions for a number of operating conditions, including the complete starting transient. Excellent correlation between the experimental and simulated results is obtained which validates the Torus machine modeling approach.

Original language	English
Pages (from-to)	555-569
Number of pages	15
Journal	Electric Power Components and Systems
Volume	32
Issue number	6
DOIs	https://doi.org/10.1080/15325000490228405
Publication status	Published - Jun 2004

Keywords

Motor control
SPICE modeling
Torus motor drives

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1080/15325000490228405

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title = "Dynamic model of Torus motor drive using ANN and FSE methods for the back EMF estimation",

abstract = "In this article, two dynamic models of the Torus machine are discussed. The first model uses the Fourier series expansion for the back emf and is implemented with PSpice. The second model uses the neural network estimation of the back emf and is implemented with Matlab/Simulink. The models may be used to study the steady-state as well as the transient performances of the machine operating as a motor or as a generator. Experimental results are compared with Matlab/Simulink and PSpice predictions for a number of operating conditions, including the complete starting transient. Excellent correlation between the experimental and simulated results is obtained which validates the Torus machine modeling approach.",

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AU - Al-Badi, A. H.

AU - Gastli, A.

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N2 - In this article, two dynamic models of the Torus machine are discussed. The first model uses the Fourier series expansion for the back emf and is implemented with PSpice. The second model uses the neural network estimation of the back emf and is implemented with Matlab/Simulink. The models may be used to study the steady-state as well as the transient performances of the machine operating as a motor or as a generator. Experimental results are compared with Matlab/Simulink and PSpice predictions for a number of operating conditions, including the complete starting transient. Excellent correlation between the experimental and simulated results is obtained which validates the Torus machine modeling approach.

AB - In this article, two dynamic models of the Torus machine are discussed. The first model uses the Fourier series expansion for the back emf and is implemented with PSpice. The second model uses the neural network estimation of the back emf and is implemented with Matlab/Simulink. The models may be used to study the steady-state as well as the transient performances of the machine operating as a motor or as a generator. Experimental results are compared with Matlab/Simulink and PSpice predictions for a number of operating conditions, including the complete starting transient. Excellent correlation between the experimental and simulated results is obtained which validates the Torus machine modeling approach.

KW - Motor control

KW - SPICE modeling

KW - Torus motor drives

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SN - 1532-5008

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Dynamic model of Torus motor drive using ANN and FSE methods for the back EMF estimation

Abstract

Keywords

ASJC Scopus subject areas

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