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Robust shrinking ellipsoid model predictive control for linear parameter varying system

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  • Zhang Longge
  • Yan Yan

Abstract

In this paper, a new off-line model predictive control strategy is presented for a kind of linear parameter varying system with polytopic uncertainty. A nest of shrinking ellipsoids is constructed by solving linear matrix inequality. By splitting the objective function into two parts, the proposed strategy moves most computations off-line. The on-line computation is only calculating the current control to assure the system shrinking into the smaller ellipsoid. With the proposed formulation, the stability of the closed system is proved, followed with two numerical examples to demonstrate the proposed method’s effectiveness in the end.

Suggested Citation

  • Zhang Longge & Yan Yan, 2017. "Robust shrinking ellipsoid model predictive control for linear parameter varying system," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-13, June.
  • Handle: RePEc:plo:pone00:0178625
    DOI: 10.1371/journal.pone.0178625
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    Cited by:

    1. Daniel Rodriguez-Guevara & Antonio Favela-Contreras & Francisco Beltran-Carbajal & David Sotelo & Carlos Sotelo, 2021. "Active Suspension Control Using an MPC-LQR-LPV Controller with Attraction Sets and Quadratic Stability Conditions," Mathematics, MDPI, vol. 9(20), pages 1-17, October.
    2. Yan Yan & Longge Zhang, 2021. "Robust Model Predictive Control with Almost Zero Online Computation," Mathematics, MDPI, vol. 9(3), pages 1-10, January.

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