A motor control method by using Machine learning

Kano Matsuura, Kan Akatsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is believed that further popularization of highly efficient PMSM in recent years can contribute to energy consumption reduction. Therefore, further development of electric motor technology is required. The control method that can deal with nonlinear elements is proposed by performing control using RT-simulation. However, the conventional RT-simulation based control can not cope with changes in motor parameters. To solve this problem, We propose to make the motor model which can respond with the change of motor parameters by using machine learning algorithm.

Original languageEnglish
Title of host publication23rd International Conference on Electrical Machines and Systems, ICEMS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages652-655
Number of pages4
ISBN (Electronic)9784886864192
DOIs
Publication statusPublished - 2020 Nov 24
Event23rd International Conference on Electrical Machines and Systems, ICEMS 2020 - Hamamatsu, Japan
Duration: 2020 Nov 242020 Nov 27

Publication series

Name23rd International Conference on Electrical Machines and Systems, ICEMS 2020

Conference

Conference23rd International Conference on Electrical Machines and Systems, ICEMS 2020
CountryJapan
CityHamamatsu
Period20/11/2420/11/27

Keywords

  • machine-learning
  • Motor-control
  • neural network
  • Non-linear element
  • PMSM
  • RT-simulator

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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