• DocumentCode
    390993
  • Title

    Ellipsoidal low-demanding MPC schemes for uncertain polytopic discrete-time systems

  • Author

    Angeli, David ; Casavola, Alessandro ; Mosca, Edoardo

  • Author_Institution
    Dip. di Sistemi e Informatica, Univ. di Firenze, Italy
  • Volume
    3
  • fYear
    2002
  • fDate
    10-13 Dec. 2002
  • Firstpage
    2935
  • Abstract
    A model predictive control (MPC) method based on ellipsoidal calculus is described in order to address the control problems in the presence of state and input constraints for uncertain polytopic linear plants under persistent disturbances. In order to reduce the usually high numerical complexity and conservatism associated to polytopic robust MPC schemes the present approach consists of moving off-line most part of the computational burden and using closed-loop predictions. An example is also presented.
  • Keywords
    closed loop systems; discrete time systems; linear matrix inequalities; linear systems; predictive control; state feedback; uncertain systems; closed-loop predictions; discrete-time systems; ellipsoidal calculus; inner approximation criterion; linear matrix inequality; linear systems; model predictive control; polytopic systems; state-feedback; uncertain systems; Control systems; Predictive models; Robust control; Robustness; Stability; State-space methods; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2002, Proceedings of the 41st IEEE Conference on
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-7516-5
  • Type

    conf

  • DOI
    10.1109/CDC.2002.1184300
  • Filename
    1184300