Predictive Error Model-Based Enhanced Observer for PMSM Deadbeat Control Systems

Dongliang Ke, Fengxiang Wang, Xinhong Yu, S. Alireza Davari, Ralph Kennel

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

To achieve high robustness and performance, this article proposes an enhanced observer based on a predictive error model for the deadbeat predictive current control method (DPCC-PEMO). First, the mathematical model of permanent magnet synchronous motor (PMSM), deadbeat predictive current control (DPCC) method, and disturbance analysis are presented. Second, to estimate the trend of current variation in advance under nonlinear disturbance effect of model mismatch, the predictive error model is designed based on the recursive least squares (RLS) algorithm. Furthermore, the enhanced observer combined with the predictive error model (PEMO) is proposed, and its stability and high convergence are proved. Finally, utilizing the PEMO, the predictive current model is established and the proposed DPCC method is developed. The experimental results validate the strong robustness and excellent dynamic tracking performance of the proposed method in PMSM systems.

Original languageEnglish
Pages (from-to)2242-2252
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume71
Issue number3
DOIs
StatePublished - 1 Mar 2024

Keywords

  • Deadbeat predictive current control (DPCC)
  • observer
  • permanent magnet synchronous motor (PMSM)
  • predictive error model (PEMO)

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