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Identification of Induction Machine Parameters Using a New Adaptive Genetic Algorithm

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Interests in seeking accurate and reliable parameters for identification methods of induction machines constitute major modeling concerns for performance prediction and assessment. This article presents an optimization, technique-based, parameters identification for the machine steady-state operation. This method is based on a genetic algorithm incorporating a new adaptive scheme for a computing time reduction. It aims to accurately identify the parameters by solving a nonlinear curve fitting problem. Finally, the obtained machine performances of the adaptive genetic algorithm method are compared with both reference and near-least-square-error estimator using experimental variable load measurements.

Keywords: adaptive GA; identification method; induction machines; optimization technique

Document Type: Research Article


Affiliations: Dept. of Electrical Engineering, University of Batna, Batna, Algeria

Publication date: August 1, 2004

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