Parameters estimation of nonlinear models of DC motors using neural networks

I. F. El-Arabawy; H. A. Yousef; M. Z. Mostafa; H. M. Abdulkader

doi:10.1109/IECON.2000.972582

Parameters estimation of nonlinear models of DC motors using neural networks

I. F. El-Arabawy, H. A. Yousef, M. Z. Mostafa, H. M. Abdulkader

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

This paper considers the development of an estimation scheme for parameters of nonlinear models of dc motors using neural network. The neural network used in this paper is a linear recurrent neural network. This scheme is considered as an on line identification method based on minimization of the least square error between the actual and the estimated parameters. The stability and convergence of the proposed estimation scheme are presented. Numerical results show the effectiveness of the proposed scheme for parameters estimation of nonlinear model of a dc series motor.

Original language	English
Title of host publication	IECON Proceedings (Industrial Electronics Conference)
Publisher	IEEE Computer Society
Pages	1997-2000
Number of pages	4
DOIs	https://doi.org/10.1109/IECON.2000.972582
Publication status	Published - 2000
Externally published	Yes

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
Volume	1

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/IECON.2000.972582

Cite this

El-Arabawy, I. F., Yousef, H. A., Mostafa, M. Z., & Abdulkader, H. M. (2000). Parameters estimation of nonlinear models of DC motors using neural networks. In IECON Proceedings (Industrial Electronics Conference) (pp. 1997-2000). Article 972582 (IECON Proceedings (Industrial Electronics Conference); Vol. 1). IEEE Computer Society. https://doi.org/10.1109/IECON.2000.972582

Parameters estimation of nonlinear models of DC motors using neural networks. / El-Arabawy, I. F.; Yousef, H. A.; Mostafa, M. Z. et al.
IECON Proceedings (Industrial Electronics Conference). IEEE Computer Society, 2000. p. 1997-2000 972582 (IECON Proceedings (Industrial Electronics Conference); Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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abstract = "This paper considers the development of an estimation scheme for parameters of nonlinear models of dc motors using neural network. The neural network used in this paper is a linear recurrent neural network. This scheme is considered as an on line identification method based on minimization of the least square error between the actual and the estimated parameters. The stability and convergence of the proposed estimation scheme are presented. Numerical results show the effectiveness of the proposed scheme for parameters estimation of nonlinear model of a dc series motor.",

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AU - Mostafa, M. Z.

AU - Abdulkader, H. M.

PY - 2000

Y1 - 2000

N2 - This paper considers the development of an estimation scheme for parameters of nonlinear models of dc motors using neural network. The neural network used in this paper is a linear recurrent neural network. This scheme is considered as an on line identification method based on minimization of the least square error between the actual and the estimated parameters. The stability and convergence of the proposed estimation scheme are presented. Numerical results show the effectiveness of the proposed scheme for parameters estimation of nonlinear model of a dc series motor.

AB - This paper considers the development of an estimation scheme for parameters of nonlinear models of dc motors using neural network. The neural network used in this paper is a linear recurrent neural network. This scheme is considered as an on line identification method based on minimization of the least square error between the actual and the estimated parameters. The stability and convergence of the proposed estimation scheme are presented. Numerical results show the effectiveness of the proposed scheme for parameters estimation of nonlinear model of a dc series motor.

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M3 - Conference contribution

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BT - IECON Proceedings (Industrial Electronics Conference)

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Parameters estimation of nonlinear models of DC motors using neural networks

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