Parameters estimation of nonlinear models of DC motors using neural networks

Author

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

Author_Institution

Fac. of Eng., Alexandria Univ., Egypt

Volume

3

fYear

2000

fDate

2000

Firstpage

1997

Abstract

This paper considers the development of an estimation scheme for parameters of nonlinear models of DC motors using neural networks. The neural network used in this paper is a linear recurrent neural network. This scheme is considered as an online 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

Keywords

DC motors; control system analysis; least squares approximations; machine control; machine theory; neural nets; parameter estimation; DC motors; control simulation; convergence; least square error minimization; linear recurrent neural network; nonlinear models parameter estimation; online identification method; stability; Buildings; DC motors; Least squares approximation; Multi-layer neural network; Neural networks; Nonlinear dynamical systems; Parameter estimation; Power system modeling; Recurrent neural networks; Velocity control;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE

Conference_Location

Nagoya

Print_ISBN

0-7803-6456-2

Type

conf

DOI

10.1109/IECON.2000.972582

Filename

972582