Extended-State-Observer-Based Model Predictive Power Control for Three-Level NPC Rectifiers with Inductance Estimation

Chenhui Yu, Fengxiang Wang, Guiying Lin, Cristian Garcia, Jose Rodriguez

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

1 Citation (Scopus)

Abstract

In the classical model predictive control strategy, parameter variation will affect the system performance. In this paper, an extended-state-observer-based model predictive power control (ESOB-MPPC) strategy for three-level neutral point clamped (NPC) rectifiers is presented. Firstly, the system model is designed by taking into consideration the system uncertainties and the external disturbance. Secondly, inductance is estimated by forgetting factor recursive least squares (FFRLS) algorithm for the enhanced parameter robustness. Simulation results verify that the proposed method has good dynamic performance and parameter robustness.

Original languageEnglish
Title of host publication2020 IEEE 9th International Power Electronics and Motion Control Conference, IPEMC 2020 ECCE Asia
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2622-2626
Number of pages5
ISBN (Electronic)9781728153018
DOIs
Publication statusPublished - 29 Nov 2020
Event9th IEEE International Power Electronics and Motion Control Conference, IPEMC 2020 ECCE Asia - Nanjing, China
Duration: 29 Nov 20202 Dec 2020

Publication series

Name2020 IEEE 9th International Power Electronics and Motion Control Conference, IPEMC 2020 ECCE Asia

Conference

Conference9th IEEE International Power Electronics and Motion Control Conference, IPEMC 2020 ECCE Asia
Country/TerritoryChina
CityNanjing
Period29/11/202/12/20

Keywords

  • Extended state observer
  • forgetting factor recursive least squares
  • model predictive power control
  • three-level neutral point clamped rectifiers

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Control and Optimization

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