Two alternate approaches for characterization of the terminal region for continuous time quasi-infinite horizon NMPC

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    15 Citations (Scopus)

    Abstract

    In this work, two alternate approaches are developed for characterization of the terminal region within the nominal stability framework developed by Chen and Allgower [3]. The proposed approaches directly make use of the weighting matrices in the NMPC cost function as a basis for choosing the tuning parameters required to characterize the terminal set. In the first approach, a quadratic regulator (LQR) is designed in the terminal region. It is shown that the solution of the associated algebraic Riccati equation can be directly used for the characterization of the terminal set. The second approach works with any arbitrary stabilizing linear state feedback controller designed in the terminal set and this feature provides additional flexibility to characterize the terminal set. The efficacy of the proposed approaches is demonstrated using the benchmark quadruple tank system example from the literature. The simulation studies reveal that the sizes of the terminal sets obtained using the proposed approaches are significantly higher than the size of the terminal region obtained using the approach given by Chen and Allgower [3].

    Original languageEnglish
    Title of host publication12th IEEE International Conference on Control and Automation, ICCA 2016
    PublisherIEEE Computer Society
    Pages98-103
    Number of pages6
    ISBN (Electronic)9781509017386
    DOIs
    Publication statusPublished - 07-07-2016
    Event12th IEEE International Conference on Control and Automation, ICCA 2016 - Kathmandu, Nepal
    Duration: 01-06-201603-06-2016

    Publication series

    NameIEEE International Conference on Control and Automation, ICCA
    Volume2016-July
    ISSN (Print)1948-3449
    ISSN (Electronic)1948-3457

    Conference

    Conference12th IEEE International Conference on Control and Automation, ICCA 2016
    Country/TerritoryNepal
    CityKathmandu
    Period01-06-1603-06-16

    All Science Journal Classification (ASJC) codes

    • Artificial Intelligence
    • Computer Science Applications
    • Control and Systems Engineering
    • Electrical and Electronic Engineering
    • Industrial and Manufacturing Engineering

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