• DocumentCode
    3352741
  • Title

    Economic optimality in MPC: A comparative study

  • Author

    Ferramosca, Antonio ; Gonzalez, Alejandro H. ; Limon, Daniel

  • Author_Institution
    Inst. of Technol. Dev. for the Chem. Ind. (INTEC), Univ. Nac. del Litoral (UNL), Santa Fe, Argentina
  • fYear
    2015
  • fDate
    1-3 July 2015
  • Firstpage
    2555
  • Lastpage
    2560
  • Abstract
    Model Predictive Control (MPC) is one of the most used advanced control strategy in the industries, mainly due to its capability to fulfill economic objectives, taking into account a simplified dynamic model of the plant, constraints, and stability requirements. In the last years, several economic formulations of MPC have been presented, which overcome the standard setpoint-tracking formulation. The goal of this work is to provide, by means of application to a highly nonlinear plant, a comparison of different strategies, focusing mainly on economic optimality, computational burden, and economic performance (understood as transient economic optimality).
  • Keywords
    nonlinear control systems; optimisation; predictive control; stability; MPC; economic optimality; model predictive control; nonlinear plant; setpoint-tracking formulation; stability requirement; Cost function; Economics; Inductors; Mathematical model; Polymers; Steady-state;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2015
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    978-1-4799-8685-9
  • Type

    conf

  • DOI
    10.1109/ACC.2015.7171119
  • Filename
    7171119