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 proceedingConference 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 languageEnglish
Title of host publicationIECON Proceedings (Industrial Electronics Conference)
PublisherIEEE Computer Society
Pages1997-2000
Number of pages4
Volume1
DOIs
Publication statusPublished - 2000

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Parameters estimation of nonlinear models of DC motors using neural networks'. Together they form a unique fingerprint.

  • 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) (Vol. 1, pp. 1997-2000). [972582] IEEE Computer Society. https://doi.org/10.1109/IECON.2000.972582