• DocumentCode
    2716349
  • Title

    Automatic code generation for real-time implementation of Model Predictive Control

  • Author

    Kvasnica, Michal ; Rauová, Ivana ; Fikar, Miroslav

  • Author_Institution
    Inst. of Inf. Eng., Autom., & Math., Slovak Univ. of Technol. in Bratislava, Bratislava, Slovakia
  • fYear
    2010
  • fDate
    8-10 Sept. 2010
  • Firstpage
    993
  • Lastpage
    998
  • Abstract
    Model Predictive Control (MPC) is a proven control concept with many applications in the process industry. Popularity of the framework is mainly due to its ability to optimize behavior of the process while respecting physical and economical constraints. The major challenge of implementing MPC in real time on low-cost hardware is the inherent computational complexity. To address this goal, it is proposed to solve a given MPC problem using parametric programming, which encodes the optimal control moves as a lookup table. A great advantage being that such tables can then be processed even with low computational resources and therefore allow MPC to be deployed to low cost control devices. In the paper we present a unique software tool which allows MPC problems to be designed with low human effort, and is capable to automatically generate real-time executable code for various target platforms.
  • Keywords
    computational complexity; control engineering computing; optimal control; predictive control; program compilers; automatic code generation; computational complexity; computational resources; economical constraints; low-cost hardware; model predictive control; optimal control; parametric programming; physical constraints; process industry; real-time executable code; real-time implementation; Binary search trees; Mathematical model; Optimal control; Optimization; Process control; Real time systems; Table lookup;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Aided Control System Design (CACSD), 2010 IEEE International Symposium on
  • Conference_Location
    Yokohama
  • Print_ISBN
    978-1-4244-5354-2
  • Electronic_ISBN
    978-1-4244-5355-9
  • Type

    conf

  • DOI
    10.1109/CACSD.2010.5612806
  • Filename
    5612806