Application of evolutionary algorithms with adaptive mutation to the identification of induction motor parameters at standstill

• Teresa Orlowska-Kowalska ^[1] ; Joanna Lis ^[1]
  1. [1] Institute of Electrical Machines
• Localización: Compel: International journal for computation and mathematics in electrical and electronic engineering, ISSN 0332-1649, Vol. 28, Nº 6 (Special Issue: Selected Papers from ICSC 2008), 2009, págs. 1647-1661
• Idioma: inglés
• Enlaces
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• Resumen

  • Purpose – The purpose of this paper is to obtain a preliminary off‐line identification of induction motor (IM) parameters at standstill in a reasonable calculation time, which will be useful for the initial adjustment of controllers and state observer parameters in the sensorless drive system.

    Design/methodology/approach – The identification procedure of electrical parameters of IM equivalent circuit is performed at standstill and is based on the reconstruction of the stator current response to the forced stator voltage using evolutionary algorithms (EAs) with hard selection and different mutation schemes.

    Findings – It is shown that an application of the EA with adaptive mutation mechanism based on simulated annealing method gives very good accuracy of parameters identification and the shortest execution time of the identification procedure as well in simulation as in the experimental tests.

    Research limitations/implications – The investigation looks mainly at the minimization of the execution time of the identification algorithm and on the identification accuracy performance, taking into account the good approximation of the measured stator current response.

    Practical implications – The proposed EA with the improved adaptive mutation scheme can be easily realised using modern digital signal processor (DSP), which is usually applied for control purposes of the sensorless IM drive system with vector control. The implementation is tested in experimental setup with floating point DSP used as the system controller.

    Originality/value – The application of adaptive mutation with simulated annealing in the EA with hard selection for the fast, off‐line preliminary identification of the IM parameter at standstill.