Performance prediction of SRM drive systems under normal and fault operating conditions using GA-based ANN method

Authors
Arkadan, AA Du, P Sidani, M Bouji, M
Citation
Aa. Arkadan et al., Performance prediction of SRM drive systems under normal and fault operating conditions using GA-based ANN method, IEEE MAGNET, 36(4), 2000, pp. 1945-1949
Citations number
5
Categorie Soggetti
Apllied Physucs/Condensed Matter/Materiales Science
Journal title
IEEE TRANSACTIONS ON MAGNETICS
ISSN journal
00189464 → ACNP
Volume
36
Issue
4
Year of publication
2000
Part
1
Pages
1945 - 1949
Database
ISI
SICI code
0018-9464(200007)36:4<1945:PPOSDS>2.0.ZU;2-3
Abstract
A method to predict the performance characteristics of Switched Reluctance Motor (SRM) drive systems under normal and fault operating conditions is pr esented. The method uses a Genetic Algorithm (GA) based Artificial Neural N etworks (ANN's) approach which is applied for its interpolation capabilitie s for highly nonlinear systems in order to obtain a fast and accurate predi ction of the performance of the SRM drive system.