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Robust model predictive control for fractional-order descriptor systems with uncertainty

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Abstract

In this study, a new robust predictive control technique is investigated for uncertain fractional-order descriptor systems. Using the properties of fractional calculus and the construction of an appropriate Lyapunov function, the sufficient conditions to guarantee the existence of a robust predictive controller are given by minimizing the worst-case optimization problem. The new robust predictive controller is presented by using Shur complement, linear matrix inequality toolbox and cone-complement linear algorithm, and it is proved that the feasible solution of the optimization problem at the initial time can guarantee the admissibility of fractional-order descriptor closed-loop system.

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Acknowledgements

I would like to thank the Editor and the reviewers for their effort to provide us so many constructive comments.

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Authors and Affiliations

  1. LIM (LR01ES13), EPT, University of Carthage, Carthage, Tunisia

    Adnène Arbi

  2. ENSTAB, University of Carthage, Carthage, Tunisia

    Adnène Arbi

  3. Department of Advanced Sciences and Technologies at National School of Advanced Sciences and Technologies of Borj Cedria, University of Carthage, 1164, Hammam-Chott, Tunisia

    Adnène Arbi

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  1. Adnène Arbi
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Correspondence to Adnène Arbi.

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Arbi, A. Robust model predictive control for fractional-order descriptor systems with uncertainty. Fract Calc Appl Anal 27, 173–189 (2024). https://doi.org/10.1007/s13540-023-00226-4

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  • DOI: https://doi.org/10.1007/s13540-023-00226-4

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