• DocumentCode
    2574879
  • Title

    Performance-lossless complexity reduction in Explicit MPC

  • Author

    Kvasnica, Michal ; Fikar, Miroslav

  • Author_Institution
    Inst. of Inf. Eng., Autom., & Math., Slovak Univ. of Technol. in Bratislava, Bratislava, Slovakia
  • fYear
    2010
  • fDate
    15-17 Dec. 2010
  • Firstpage
    5270
  • Lastpage
    5275
  • Abstract
    The idea of Explicit Model Predictive Control (MPC) is to find the optimal control input as an explicit Piecewise Affine (PWA) function of the initial conditions. The function, however, is often too complex to be processed by a typical control hardware setup in real time. Therefore the paper proposes a novel method of replacing a generic continuous PWA function by a different function of significantly lower complexity in such a way that optimal closed-loop performance, stability and constraint satisfaction are preserved. The idea is based on eliminating a significant portion of the regions of the PWA function over which the function attains a saturated value. An extensive case study is presented which confirms that a significant reduction of complexity is achieved in general.
  • Keywords
    closed loop systems; optimal control; predictive control; stability; constraint satisfaction; explicit model predictive control; explicit piecewise affine function; optimal closed-loop performance; optimal control input; performance-lossless complexity reduction; stability; Complexity theory; Hardware; Indexes; Joints; Memory management; Merging; Optimal control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2010 49th IEEE Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4244-7745-6
  • Type

    conf

  • DOI
    10.1109/CDC.2010.5717578
  • Filename
    5717578