Efficient finite-position-set MRAS observer for encoder-less control of DFIGs

Mohamed Abdelrahem, Ralph Kennel, Christoph Hackl, Mehmet Dal, Jose Rodriguez

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

8 Citations (Scopus)

Abstract

This work introduces an efficient finite-position-set model-reference adaptive system (FPS-MRAS) estimator for sensor-less control of a doubly fed induction generator (DFIG) in a variable speed wind energy conversion system (WECS). The idea of the proposed FPS-MRAS is derived from the finite-control-set model predictive control (FCS-MPC) principle, i.e. a limited set of angles for the rotor position are employed to predict the rotor current of the DFIG. Subsequently, the optimal angle for the rotor position is the one that its prediction optimizes a pre-defined (novel) quality function. Accordingly, the constant-gain proportional-integral (CG-PI) regulator and its tedious tuning which is normally used in MRAS observers is not required. The estimation response of the suggested FPS-MRAS observer is investigated by experiments and compared with the performance of the classical MRAS under different operation conditions and at variations of the DFIG parameters.

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

  • DF1Gs
  • MKAS observer
  • Model predictive control
  • Wind turbines

ASJC Scopus subject areas

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

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