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    Improvement of the Control System Performance based on Fractional-Order PID Controllers and Models with Robustness Considerations

    Access Status
    Fulltext not available
    Authors
    Meneses, H.
    Guevara, E.
    Arrieta, O.
    Padula, Fabrizio
    Vilanova, R.
    Visioli, A.
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Meneses, H. and Guevara, E. and Arrieta, O. and Padula, F. and Vilanova, R. and Visioli, A. 2018. Improvement of the Control System Performance based on Fractional-Order PID Controllers and Models with Robustness Considerations, pp. 551-556.
    Source Title
    IFAC-PapersOnLine
    DOI
    10.1016/j.ifacol.2018.06.153
    ISSN
    2405-8963
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    Funding and Sponsorship
    http://purl.org/au-research/grants/arc/DP160104994
    URI
    http://hdl.handle.net/20.500.11937/69893
    Collection
    • Curtin Research Publications
    Abstract

    © 2018 In this paper we assess the performance improvement achievable by using onedegree-of-freedom fractional-order proportional-integral-derivative controllers (FOPI/FOPID) instead of their integer-order counterparts (PI/PID). To this end, we take into account a single-pole fractional-order model, which has the advantage of representing a wide variety of process dynamics, ranging from over-damped (first-order models) to under-damped behaviors, depending on the fractional order a. In the proposed analysis we consider a combined performance index which deals with the trade-off between servo and regulatory control modes. Moreover, the performance of the closed-loop system is optimized subject to a robustness constraint, expressed as a target maximum sensitivity of either 1.4 or 2.0. The obtained performance assessment results are shown for different values of the fractional order a of the model and for different normalized dead times, thus quantitatively evaluating the benefits achievable with fractional controllers on a wide variety of process dynamics.

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