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)


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
Number of pages4
Publication statusPublished - 2000

Publication series

NameIECON Proceedings (Industrial Electronics Conference)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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