Linear parameter-varying techniques for control of a magnetic bearing system

Bei Lu (Corresponding Author), Heeju Choi, Gregory Buckner, Kari Tammi

    Research output: Contribution to journalArticleScientificpeer-review

    49 Citations (Scopus)

    Abstract

    In this paper, a linear parameter-varying (LPV) control design method is evaluated experimentally on an active magnetic bearing (AMB) system. A speed-dependent LPV model of the AMB system is derived. Model uncertainties are identified using artificial neural networks, and an uncertainty weighting function is approximated for LPV control synthesis. Experiments are conducted to verify the robustness of LPV controllers for a wide range of rotational speed. This LPV control approach eliminates the need for gain-scheduling, and provides better performance than the traditional proportional-integral-derivative control for high-speed operation.
    Original languageEnglish
    Pages (from-to)1161 - 1172
    Number of pages12
    JournalControl Engineering Practice
    Volume16
    DOIs
    Publication statusPublished - 2008
    MoE publication typeA1 Journal article-refereed

    Fingerprint

    Magnetic Bearing
    Magnetic bearings
    Active Magnetic Bearing
    Gain Scheduling
    Robustness (control systems)
    Weighting Function
    Model Uncertainty
    Control Design
    Scheduling
    Design Method
    Artificial Neural Network
    Derivatives
    Neural networks
    High Speed
    Eliminate
    Controllers
    Directly proportional
    Synthesis
    Verify
    Robustness

    Cite this

    Lu, Bei ; Choi, Heeju ; Buckner, Gregory ; Tammi, Kari. / Linear parameter-varying techniques for control of a magnetic bearing system. In: Control Engineering Practice. 2008 ; Vol. 16. pp. 1161 - 1172.
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    Linear parameter-varying techniques for control of a magnetic bearing system. / Lu, Bei (Corresponding Author); Choi, Heeju; Buckner, Gregory; Tammi, Kari.

    In: Control Engineering Practice, Vol. 16, 2008, p. 1161 - 1172.

    Research output: Contribution to journalArticleScientificpeer-review

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    AU - Choi, Heeju

    AU - Buckner, Gregory

    AU - Tammi, Kari

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    AB - In this paper, a linear parameter-varying (LPV) control design method is evaluated experimentally on an active magnetic bearing (AMB) system. A speed-dependent LPV model of the AMB system is derived. Model uncertainties are identified using artificial neural networks, and an uncertainty weighting function is approximated for LPV control synthesis. Experiments are conducted to verify the robustness of LPV controllers for a wide range of rotational speed. This LPV control approach eliminates the need for gain-scheduling, and provides better performance than the traditional proportional-integral-derivative control for high-speed operation.

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    EP - 1172

    JO - Control Engineering Practice

    JF - Control Engineering Practice

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