Abstract
A method to predict the performance characteristics of switched reluctance motor (SRM) drive systems under normal and fault operating conditions is presented. The method uses a genetic algorithm (GA) based artificial neural networks (ANNs) approach which is applied for its interpolation capabilities for highly nonlinear systems in order to obtain a fast and accurate prediction of the performance of the SRM drive system.
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