• DocumentCode
    707115
  • Title

    Fault-tolerant control of a ship propulsion system using model predictive control

  • Author

    Kerrigan, E.C. ; Maciejowski, J.M.

  • Author_Institution
    Dept. of Eng., Univ. of Cambridge, Cambridge, UK
  • fYear
    1999
  • fDate
    Aug. 31 1999-Sept. 3 1999
  • Firstpage
    4602
  • Lastpage
    4607
  • Abstract
    Recently, it has been shown how model predictive control (MPC) can adapt to faults in certain circumstances. This paper describes how MPC was successfully implemented as a fault-tolerant controller for a single engine/propeller model of a ship propulsion system. It is shown that the MPC controller can be tuned to be robust to internal faults that develop in the ship propulsion system, even in the absence of any fault detection and isolation (FDI) information for the internal faults. For the case of sensor faults, it is assumed that FDI information is available and it is shown how the MPC controller, in combination with a Kalman estimator, can drastically improve the tracking response of the system in the presence of sensor faults. The paper concludes that MPC is a very good candidate for a fault-tolerant controller for the ship propulsion system, requiring re-configuration only at the supervisory level, without the need for additional re-configuration in the lower-level control systems.
  • Keywords
    Kalman filters; control system synthesis; fault diagnosis; fault tolerant control; marine propulsion; predictive control; ships; FDI information; Kalman estimator; MPC controller; controller design; fault detection and isolation; fault-tolerant controller; model predictive control; sensor faults; ship propulsion system; single engine-propeller model; Benchmark testing; Control systems; Engines; Marine vehicles; Propellers; Shafts; fault handling; fault-tolerant control; predictive control; ship propulsion benchmark;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 1999 European
  • Conference_Location
    Karlsruhe
  • Print_ISBN
    978-3-9524173-5-5
  • Type

    conf

  • Filename
    7100061