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 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering
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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