Improved Model Predictive Current Control of PMSM based on Luenberger Observer

Xiangdong Liu, Wenkai Li, Zhen Chen, Yan Li, Congzhe Gao, Haoyu Wang

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

1 Citation (Scopus)

Abstract

Model predictive current control (MPCC) of PMSM is a control tactics with great potential. Compared with the traditional current control method, it has excellent advantages in simply constructed structure and dynamic reply rate. It is also applicable to the consideration of nonlinear factors and constraints of the system. However, the PMSM control system has the characteristics of strong coupling and time-varying parameters. As a result, the predictive model is apt to be mismatched, which leads to prediction error and control performance degradation of MPCC. Aiming at the problem of parameter mismatches and sampling delay, the Luenberger state observer is proposed. The simulation results show that the MPCC based on Lunberger observer can effectively suppress the influences of motor parameter disturbances, which verifies the effectiveness of the MPCC method.

Original languageEnglish
Title of host publicationProceeding - 2021 China Automation Congress, CAC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3084-3089
Number of pages6
ISBN (Electronic)9781665426473
DOIs
Publication statusPublished - 2021
Event2021 China Automation Congress, CAC 2021 - Beijing, China
Duration: 22 Oct 202124 Oct 2021

Publication series

NameProceeding - 2021 China Automation Congress, CAC 2021

Conference

Conference2021 China Automation Congress, CAC 2021
Country/TerritoryChina
CityBeijing
Period22/10/2124/10/21

Keywords

  • Lunberger state observer
  • Model predictive current control
  • PMSM

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