Current Sensorless Model Predictive Control of Matrix Converter With Zero Common-Mode Voltage

Ali Sarajian, Quanxue Guan, Patrick Wheeler, Davood Arab Khaburi, Ralph Kennel, Jose Rodriquez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

To eliminate the common-mode voltage (CMV) for matrix converters, this paper proposes a current sensorless model predictive control with reduced calculation overhead. In contrast to other traditional CMV-reducing methods which use all permissible switching configurations, this method synthesizes the output voltage and the input current with only six rotating vectors that lead to zero CMV. The proposed technique does not need to predict future load currents and source currents for those six rotating vectors, which provides another advantage in term of computation efficiency. Additionally, all current sensors are removed by using a Luenberger state observer instead in the control loop for cost reduction. The effectiveness of the proposed method is evaluated through simulation in different operation conditions.

Original languageEnglish
Title of host publicationIECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
ISBN (Electronic)9781665480253
DOIs
StatePublished - 2022
Event48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 - Brussels, Belgium
Duration: 17 Oct 202220 Oct 2022

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2022-October
ISSN (Print)2162-4704
ISSN (Electronic)2577-1647

Conference

Conference48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022
Country/TerritoryBelgium
CityBrussels
Period17/10/2220/10/22

Keywords

  • Luenberger observer
  • Matrix converter
  • model predictive control

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