Design of a Fuzzy Linear Quadratic Regulator for the Speed Control of SPMSM

Kursad M. Gul*, Ayhan Kural, Tufan Kumbasar

*Corresponding author for this work

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

Abstract

Surface-Mounted Permanent Magnet Synchronous Machines (SPMSM) operate in wide torque-speed envelopes which impose the necessity of designing an effective control system to prevent performance degradation. However, the conventional Cascade PI (CPI) control structure is still utilized in the vast majority of SPMSM applications even though it becomes inadequate against emerging nonlinearities in different operating regions. In this paper, we propose a Fuzzy Linear Quadratic Regulator (F-LQR) for the speed control of SPMSMs to maintain robustness while improving the speed control performance. We designed a Single input Fuzzy Logic Controller (SFLC) to manipulate the error compensation dynamics of the LQR to improve reference tracking and disturbance rejection performances. We employed a geometrical analysis approach when designing the SFLC which enables us to explicitly shape the fuzzy mapping with just two parameters. The practical design goals considered in the design phase of LQR and SFLC are determined by taking into account the physical limitations of the inverter board as well as the system dynamics of the SPMSM. We experimentally analyzed and compared the performances of the proposed F-LQR, LQR, and CPI on the real-world SPMSM test setup with two inclusive test scenarios. The comparative test results revealed that the proposed F-LQR improves the speed control performance while maintaining the robustness of the control system when compared to LQR and CPI.

Original languageEnglish
Title of host publicationIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
EditorsCengiz Kahraman, Irem Ucal Sari, Basar Oztaysi, Sezi Cevik Onar, Selcuk Cebi, A. Çağrı Tolga
PublisherSpringer Science and Business Media Deutschland GmbH
Pages692-699
Number of pages8
ISBN (Print)9783031397769
DOIs
Publication statusPublished - 2023
EventIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference - Istanbul, Turkey
Duration: 22 Aug 202324 Aug 2023

Publication series

NameLecture Notes in Networks and Systems
Volume759 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Country/TerritoryTurkey
CityIstanbul
Period22/08/2324/08/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Fuzzy control
  • LQR
  • SPMSM
  • vector control

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