<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper presents the problem of the identifying parameters for use in mathematical models of induction motors with the use of a genetic algorithm (GA). The effect of arithmetical crossover and the generation of new populations on identification results is analysed. The identified parameters of the model were determined as a result of the minimisation of the performance index defined as the mean-square error of stator current and angular velocity. The experiments were performed for the low power induction motor. The steady-state genetic algorithm with regard to convergence and accuracy of the identification process and calculation time is analysed.</p></abstract>

This paper presents the problem of the identifying parameters for use in mathematical models of induction motors with the use of a genetic algorithm (GA). The effect of arithmetical crossover and the generation of new populations on identification results is analysed. The identified parameters of the model were determined as a result of the minimisation of the performance index defined as the mean-square error of stator current and angular velocity. The experiments were performed for the low power induction motor. The steady-state genetic algorithm with regard to convergence and accuracy of the identification process and calculation time is analysed.

The Generating New Individuals of the Population in the Parametric Identification of the Induction Motor Problem with the Use of the Genetic Algorithm

Department of Control & Management Systems, Faculty of Electrical Engineering, Automatic Control and Computer Science

Technical Transactions

This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 Public License.

This paper presents the problem of the identifying parameters for use in mathematical models of induction motors with the use of a genetic algorithm (GA). The...

The Generating New Individuals of the Population in the Parametric Identification of the Induction Motor Problem with the Use of the Genetic Algorithm

Published Online: May 16, 2020

Page range: 109 - 117

Received: Jan 23, 2019

DOI: https://doi.org/10.4467/2353737XCT.19.025.10161

Keywords
identification, mathematical model, induction motor, genetic algorithm, crossover

© 2020 Katarzyna Rutczyńska-Wdowiak, published by Sciendo

This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 Public License.

The Generating New Individuals of the Population in the Parametric Identification of the Induction Motor Problem with the Use of the Genetic Algorithm

Published Online: May 16, 2020

Page range: 109 - 117

Received: Jan 23, 2019

DOI: https://doi.org/10.4467/2353737XCT.19.025.10161

Keywordsidentification, mathematical model, induction motor, genetic algorithm, crossover

© 2020 Katarzyna Rutczyńska-Wdowiak, published by Sciendo

This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 Public License.

Keywords
identification, mathematical model, induction motor, genetic algorithm, crossover