Multiobjective genetic estimation to induction motor parameters
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Date
2007
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Publisher
IEEE
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info:eu-repo/semantics/closedAccess
Abstract
In order to simplify the offline identification of induction motor parameters, a method based on optimization using a multiobjective genetic algorithm is proposed. The non-dominated sorting genetic algorithm (NSGA-II) is used to minimize the error between the actual data and an estimated model. The robustness of the method is shown by identifying parameters of the induction motor in three different cases. The simulation results show that the method successfully estimates the motor parameters.
Description
Joint Conference on Electromotion/IEEE Aegean Conference on Electrical Machines and Power Electronics/ -- SEP 10-12, 2007 -- Bodrum, TURKEY
Keywords
multiobjective genetic algorithm, induction motor, parameter estimation
Journal or Series
INTERNATIONAL AEGEAN CONFERENCE ON ELECTRICAL MACHINES AND POWER ELECTRONICS & ELECTROMOTION, PROCEEDINGS
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