A methodology for characterizing fault tolerant switched reluctance motors using neurogenetically derived models |
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| Authors: | Belfore L.A. II Arkadan A. |
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| Affiliation: | Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA; |
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| Abstract: | This paper examines the feasibility of using artificial neural networks (ANNs) and genetic algorithms (GAs) to develop discrete time dynamic models for fault free and faulted switched-reluctance-motor (SRM) drive systems. The results of using the ANN-GA-based (neurogenetic) model to predict the performance characteristics of a prototype SRM drive motor under normal and abnormal operating conditions are presented and verified by comparison to test data. |
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