Modulated Model-Predictive Integral Control applied to a Synchronous Reluctance Motor Drive

Jacopo Riccio, Petros Karamanakos, Shafiq Odhano, Mi Tang, Mauro Di Nardo, Giulia Tresca, Pericle Zanchetta

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper investigates an innovative modulation technique for a predictive control applied to a synchronous reluctance motor drive. The new formulation of the duty cycles, in both linear and overmodulation regions, relies on the identified flux-versus-current characteristics. Furthermore, integral terms have been introduced in the predictive control to achieve satisfactory reference tracking performance with zero steady-state error, even under model parameters mismatches. Low current ripple with smooth and fast dynamic responses are achievable at fixed switching frequency over the whole current operating range. Simulations and experimental evidence show the effectiveness of the proposed controller against standard controllers such as field-oriented current control and deadbeat current control, guaranteeing low current ripple, robustness against parameters variations, and fast dynamic performance.

Original languageEnglish
Pages (from-to)3000-3010
JournalIEEE Journal of Emerging and Selected Topics in Power Electronics
Volume11
Issue number3
Early online date14 Feb 2023
DOIs
Publication statusPublished - 2023
Publication typeA1 Journal article-refereed

Keywords

  • Computational modeling
  • Current control
  • current control
  • Heuristic algorithms
  • integral action
  • modulated model-predictive control
  • overmodulation
  • Predictive control
  • Predictive models
  • Switches
  • Switching frequency
  • Synchronous reluctance machine
  • two-level voltage-source inverter

Publication forum classification

  • Publication forum level 2

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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