• DocumentCode
    1757508
  • Title

    Distributed Model Predictive Control: An Overview and Roadmap of Future Research Opportunities

  • Author

    Negenborn, Rudy R. ; Maestre, J.M.

  • Author_Institution
    Dept. of Maritime & Transp. Technol., Delft Univ. of Technol., Delft, Netherlands
  • Volume
    34
  • Issue
    4
  • fYear
    2014
  • fDate
    Aug. 2014
  • Firstpage
    87
  • Lastpage
    97
  • Abstract
    Model-predictive control (MPC) is an optimization-based control technique that uses 1) a mathematical model of a system to predict the system´s behavior over a given horizon, 2) an objective function that represents what system behavior is desirable, 3) a mathematical formalization of operational constraints that have to be satisfied, 4) measurements of the state of the system at each time step, and 5) any information regarding upcoming disturbances that may be available. This article surveyed and categorized 35 distributed MPC approaches. Subsequently, several of the insights gained from the survey were presented. This study provides a picture of what features have received more or less attention over the last years, bringing about potential research niches for new approaches.
  • Keywords
    optimal control; optimisation; predictive control; MPC; distributed model predictive control; mathematical formalization; mathematical model; objective function; operational constraints; optimization-based control technique; system behavior prediction; Centralized control; Computer architecture; Distributed processing; Mathematical model; Optimization; Predictive control;
  • fLanguage
    English
  • Journal_Title
    Control Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1066-033X
  • Type

    jour

  • DOI
    10.1109/MCS.2014.2320397
  • Filename
    6853439