A MRAS Observer Based Sensorless Control of Doubly-Fed Reluctance Wind Turbine Generators

M. R. Agha Kashkooli, Milutin G. Jovanovic

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

    4 Citations (Scopus)

    Abstract

    A new model reference adaptive system (MRAS) based estimation technique for vector control of a brushlesss doubly fed reluctance generator (BDFRG) without a shaft position sensor is proposed. The rotor speed is being precisely observed in a closed-loop fashion through an iterative error eradication process between the measured and estimated secondary current angles in a stationary frame. Contrary to the existing MRAS designs reported in the BDFRG literature, the reference model only utilises direct measurements of the secondary currents with-out any machine parameters. Furthermore, the current estimates coming from the adaptive model are obtained using the measured grid voltages and currents, which has provided prospects for much higher accuracy and superior overall performance. The realistic simulations and the accompanying parameter sensitivity studies have shown the great controller potential for typical operating conditions of wind turbines as the main target application.

    Original languageEnglish
    Title of host publicationProceedings - IECON 2020
    Subtitle of host publication46th Annual Conference of the IEEE Industrial Electronics Society
    PublisherIEEE
    Pages1734-1739
    Number of pages6
    ISBN (Electronic)9781728154145
    DOIs
    Publication statusPublished - 18 Oct 2020
    Event46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020 - Virtual, Singapore, Singapore
    Duration: 19 Oct 202021 Oct 2020

    Publication series

    NameIECON Proceedings (Industrial Electronics Conference)
    Volume2020-October

    Conference

    Conference46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020
    Country/TerritorySingapore
    CityVirtual, Singapore
    Period19/10/2021/10/20

    Keywords

    • Adaptive Systems
    • Brushless Machines
    • Sensorless Control
    • Velocity Control
    • Wind Energy Conversion

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