An Improved Implicit Model Predictive Current Control with Continuous Control Set for PMSM Drives

Xin Jiang, Yong Yang, Mingdi Fan, Aiming Ji, Yang Xiao, Xinan Zhang, Wei Zhang, Cristian Garcia, Sergio Vazquez, Jose Rodriguez

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This paper proposes an improved implicit model predictive current control (IMPCC) method for permanent magnet synchronous motor drives. Compared to the conventional implicit MPC, the proposed IMPCC has a much lower computational burden, and thus is suitable for real-time applications. Two-step optimization is employed in this method to minimize the cost function based on continuous control set while respecting the constraints. Furthermore, the proposed IMPCC uses an incremental model that eliminates the permanent magnet flux linkage. Its strong parameter robustness against stator resistance and inductance variations is also theoretically analyzed. Experimental results are presented to show the superior performance of the proposed IMPCC.

Original languageEnglish
Pages (from-to)2444-2455
Number of pages12
JournalIEEE Transactions on Transportation Electrification
Volume8
Issue number2
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Continuous Control Set
  • Model Predictive Control
  • Parameter Mismatch
  • Permanent Magnet Synchronous Motor
  • Quadratic Program

ASJC Scopus subject areas

  • Automotive Engineering
  • Transportation
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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