• DocumentCode
    696152
  • Title

    Approaches to explicit Nonlinear Model Predictive Control with reduced partition complexity

  • Author

    Grancharova, Alexandra ; Johansen, Tor A.

  • Author_Institution
    Inst. of Control & Syst. Res., Sofia, Bulgaria
  • fYear
    2009
  • fDate
    23-26 Aug. 2009
  • Firstpage
    2414
  • Lastpage
    2419
  • Abstract
    Recently, several multi-parametric Nonlinear Programming approaches to explicit solution of constrained Nonlinear Model Predictive Control (NMPC) problems have been suggested. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation. However, the off-line computational complexity tends to increase rapidly with the number of states. In this paper, several approaches to reduce the off-line computational burden and the partition complexity of the explicit NMPC are proposed and illustrated with two examples.
  • Keywords
    computational complexity; nonlinear control systems; nonlinear programming; predictive control; constrained nonlinear model predictive control problem; explicit NMPC; multiparametric nonlinear programming approaches; offline computational burden; offline computational complexity; partition complexity; Actuators; Approximation algorithms; Approximation methods; Complexity theory; Cost function; Valves; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2009 European
  • Conference_Location
    Budapest
  • Print_ISBN
    978-3-9524173-9-3
  • Type

    conf

  • Filename
    7074767