Improved Model Predictive Current Control for SPMSM Drives with Parameter Mismatch

Xin Yuan, Shuo Zhang, Chengning Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

85 Citations (Scopus)

Abstract

Model predictive current control (MPCC) can predict future motor behavior according to a motor model. In practice, however, motor parameters will vary at run time, and the parameter mismatch disturbances caused by the variation in motor parameters will deteriorate the MPCC performance. To suppress the parameter mismatch disturbances effectively, this paper proposes a modified MPCC with a current variation update mechanism. In contrast with the traditional current prediction equation that contains crude model parameters, the modified current prediction equation contains only measured information, taking advantage of the proposed current variation update mechanism, which can update the modified prediction equation within each sampling period. A simulation established by MATLAB software indicates that the proposed method can effectively suppress the parameter mismatch disturbances. Experiments are carried out to verify the correctness of the proposed method.

Original languageEnglish
Article number8657947
Pages (from-to)852-862
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume67
Issue number2
DOIs
Publication statusPublished - Feb 2020
Externally publishedYes

Keywords

  • Model predictive current control (MPCC)
  • parameter mismatch disturbances
  • surface permanent magnet synchronous motor (SPMSM)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Improved Model Predictive Current Control for SPMSM Drives with Parameter Mismatch'. Together they form a unique fingerprint.

Cite this