• DocumentCode
    3537369
  • Title

    Design of plug-and-play model predictive control: An approach based on linear programming

  • Author

    Riverso, Stefano ; Farina, Marcello ; Ferrari-Trecate, Giancarlo

  • Author_Institution
    Dipt. di Ing. Ind. e dell´Inf., Univ. degli Studi di Pavia, Pavia, Italy
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    6530
  • Lastpage
    6535
  • Abstract
    In this paper we consider a linear system represented by subsystems coupled through states and propose a distributed control scheme for guaranteeing asymptotic stability and satisfaction of constraints on system inputs and states. Our design procedure enables Plug-and-Play (PnP) operations, meaning that (i) the addition or removal of subsystems triggers the synthesis of local controllers associated to successors to the subsystem only and (ii) the synthesis of a local controller for a subsystem requires information only from predecessors of the subsystem and it can be performed using only local computational resources. Our method, that is based on Model Predictive Control (MPC) advances the PnP design procedure proposed in [1] in several directions. Notably, we show how critical steps in the design of a local controller can be solved through linear programming.
  • Keywords
    asymptotic stability; control system synthesis; distributed control; linear programming; linear systems; predictive control; MPC; PnP design procedure; PnP operations; asymptotic stability; control design; distributed control scheme; linear programming; linear system; local controller synthesis; plug-and-play model predictive control; Algorithm design and analysis; Asymptotic stability; Bismuth; Decentralized control; Electron tubes; Linear programming; Nickel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
  • Conference_Location
    Firenze
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-5714-2
  • Type

    conf

  • DOI
    10.1109/CDC.2013.6760922
  • Filename
    6760922