Reinforcement learning control for six-phase permanent magnet synchronous motor position servo drive

Wei Lun Peng, Yung Wen Lan, Shih Gang Chen, Faa Jeng Lin, Ray I. Chang, Jan Ming Ho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Since the permanent magnet synchronous motor (PMSM) has nonlinear dynamic behavior characteristics, it is difficult to develop an ideal controller. In this paper, we develop a novel method for the six-phase PMSM (6PPMSM) position servo drive based on deep reinforcement learning (RL). Comparison studies between the proposed controller and the recurrent fuzzy neural cerebellar model articulation network (RFNCMAN) controller are presented. The results show that our controller can follow the reference trajectories more precisely in general cases, where the average tracking error obtained is 90% smaller than that of RFNCMAN.

Original languageEnglish
Title of host publicationProceedings of the 3rd IEEE International Conference on Knowledge Innovation and Invention 2020, ICKII 2020
EditorsTeen-Hang Meen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages332-335
Number of pages4
ISBN (Electronic)9781728193335
DOIs
StatePublished - 21 Aug 2020
Event3rd IEEE International Conference on Knowledge Innovation and Invention, ICKII 2020 - Kaohsiung, Taiwan
Duration: 21 Aug 202023 Aug 2020

Publication series

NameProceedings of the 3rd IEEE International Conference on Knowledge Innovation and Invention 2020, ICKII 2020

Conference

Conference3rd IEEE International Conference on Knowledge Innovation and Invention, ICKII 2020
Country/TerritoryTaiwan
CityKaohsiung
Period21/08/2023/08/20

Keywords

  • Deep deterministic policy gradient
  • Reinforcement learning
  • Servo drive system
  • Six-phase magnet synchronous motor permanent
  • Twin delayed deep deterministic policy gradient algorithm

Fingerprint

Dive into the research topics of 'Reinforcement learning control for six-phase permanent magnet synchronous motor position servo drive'. Together they form a unique fingerprint.

Cite this