A Low-Complexity Modulated Model Predictive Torque and Flux Control Strategy for PMSM Drives Without Weighting Factor

Ahmed Nasr, Chunyang Gu, Giampaolo Buticchi, Serhiy Bozhko, Chris Gerada

Research output: Journal PublicationArticlepeer-review

17 Citations (Scopus)


This article proposes a modulated model predictive torque and flux control (M2PTFC) method with low complexity for a two-level voltage source inverter (2L-VSI)-fed permanent magnet synchronous motor (PMSM). The proposed strategy aims to reduce the computation burden and simplify the control implementation of the conventional M2PTFC scheme by reducing the number of candidate voltage vectors at every control sample to the minimum (i.e., only two candidates) and eliminating the weighting factor of the cost function and its corresponding tuning procedures. For these purposes, the proposed method devotes different control objectives to the duty modulation and the cost function evaluation processes while executing them sequentially. First, aiming at torque ripple reduction, a duty modulation strategy is proposed based on the analysis of torque deviations produced by different voltage vectors, which ensures proper selection of the two candidates and restricts active voltage vectors (AVVs) that cause high deviations. Then, these candidates are evaluated based on a cost function assigned to achieve the stator flux control objective. The effectiveness of the proposed control scheme is verified through comparative assessment with the conventional M2PTFC and two existing simplified methods by means of simulation and experimental results.

Original languageEnglish
Pages (from-to)1305-1316
Number of pages12
JournalIEEE Journal of Emerging and Selected Topics in Power Electronics
Issue number2
Publication statusPublished - 17 Feb 2022


  • Computational efforts
  • control set
  • duty ratio
  • model predictive torque control
  • permanent magnet synchronous motor (PMSM)
  • torque ripple
  • weighting factor

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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