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 |
| Volume | 1 |
| DOIs | |
| Publication status | Published - 2000 |
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ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering
Cite this
Parameters estimation of nonlinear models of DC motors using neural networks. / El-Arabawy, I. F.; Yousef, H. A.; Mostafa, M. Z.; Abdulkader, H. M.
IECON Proceedings (Industrial Electronics Conference). Vol. 1 IEEE Computer Society, 2000. p. 1997-2000 972582.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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TY - GEN
T1 - Parameters estimation of nonlinear models of DC motors using neural networks
AU - El-Arabawy, I. F.
AU - Yousef, H. A.
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.
UR - http://www.scopus.com/inward/record.url?scp=84968866218&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84968866218&partnerID=8YFLogxK
U2 - 10.1109/IECON.2000.972582
DO - 10.1109/IECON.2000.972582
M3 - Conference contribution
VL - 1
SP - 1997
EP - 2000
BT - IECON Proceedings (Industrial Electronics Conference)
PB - IEEE Computer Society
ER -