Modulated model predictive control of two-stage matrix converter for reducing common-mode voltage

Fengxiang Wang, Ningke Chen, Anjun Xia, Jose Rodriguez

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

6 Citations (Scopus)

Abstract

In this paper, a new kind method for two-stage matrix converter to reduce common-mode voltage (CMV) denoted as modulated model predictive control M2 PC is presented. This method combines model predictive control (MPC) and space vector modulate (SVM) with little hardware changing in general topology. The proposed method can reduce CMV influence effectively and high quality output waveforms with low distortion are obtained. In this paper, three new strategies of typical M2 PC for reducing CMV proposed and compared with that of MPC in simulation using Matlab/Simulink. A good simulation result demonstrates the effect of proposed method fore-mentioned.

Original languageEnglish
Title of host publicationProceedings - PRECEDE 2019
Subtitle of host publication2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538694145
DOIs
Publication statusPublished - 1 May 2019
Event2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019 - Quanzhou, China
Duration: 31 May 20192 Jun 2019

Publication series

NameProceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics

Conference

Conference2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019
Country/TerritoryChina
CityQuanzhou
Period31/05/192/06/19

Keywords

  • Common-mode voltage(CMV)
  • Modulated model predictive contro1 (M2PC)
  • Two-stage matrix converter(TSMC)
  • Zero vector

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization

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