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    Multivariable intermittent control (MIC) offers stability and flexibility for unstable systems. Its sensitivity to parameter inaccuracies, while challenging, can be leveraged for adaptive control and improved system performance.

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    Area of Science:

    • Control Engineering
    • Systems Theory
    • Applied Mathematics

    Background:

    • Multivariable intermittent control (MIC) integrates continuous-time optimal control with discrete state sampling.
    • MIC aims to provide stability and flexibility for controlling unstable systems.
    • System stability is typically independent of sample interval when using accurate model parameters.

    Purpose of the Study:

    • To investigate the sensitivity of MIC to inaccurate physical system parameter values.
    • To determine if this sensitivity is a limitation or a beneficial characteristic for adaptive control.
    • To explore the role of prediction error in identifying stable parameter combinations.

    Main Methods:

    • Analysis of MIC's closed-loop stability concerning model parameter inaccuracies.
    • Examination of the relationship between prediction error and physical parameter values.
    • Evaluation of prediction error as a trigger for state sampling events.

    Main Results:

    • High-dimensional parameter spaces with unstable open-loop systems present a "needle in a haystack" challenge for accurate parameter identification.
    • Prediction error, sensitive to model inaccuracies, effectively identifies parameter combinations yielding stable closed-loop control and low state error.
    • The sensitivity of prediction error to model inaccuracy is demonstrated as a valuable asset for adaptation.

    Conclusions:

    • The sensitivity of MIC to parameter inaccuracies is not solely a drawback but a potential asset for adaptive control.
    • Prediction error serves as a crucial indicator for identifying optimal parameter sets and facilitating system adaptation.
    • MIC's inherent sensitivity supports its rationale for combining robust control with operational flexibility.