Improved Genetic Algorithm Identification of the Squirrel-Cage Induction Machine Parameters
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In this paper we propose a parameter identification technique of induction machine, based on optimization techniques by genetic algorithms. This technique allows us an accurate determination of the model parameters of the IM used in static regime as well as dynamic regime and offering a better representation of the IM. Genetic algorithms have proven their interest in solving various optimization problems. In this paper we express and formulate the identification problem in the form of optimization problem by correctly choosing the fitness function and constraints adapted to our case. The validation of the genetic algorithm identification, by simulation in Matlab, has proven its accuracy and effectiveness.
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