• DocumentCode
    2464542
  • Title

    Nonlinear observers for closed-loop control of a combustion engine test bench

  • Author

    Reale, G. ; Ortner, P. ; Re, L. Del

  • fYear
    2009
  • fDate
    10-12 June 2009
  • Firstpage
    4648
  • Lastpage
    4653
  • Abstract
    In this article we compare the performance of four nonlinear state observers for a combustion engine test bench simulator including combustion oscillations, noisy measurements and disturbed inputs. These observers are the high-gain observer (HGO), the sliding-mode observer (SMO), the nonlinear extended state observer (NESO) and the extended Kalman Filter (EKF). The different observers are compared in open-loop in terms of the mean quadratic estimation error, computing time and convergence rate. A first important result obtained is that the NESO performance is good, although it does not need to know the engine friction model. Then the best of these is compared in closed-loop with a partial Luenberger observer which requires the knowledge of the model of the combustion oscillations. It turns out that we can achieve similar tracking results without the knowledge of the combustion oscillations model.
  • Keywords
    Kalman filters; closed loop systems; combustion; engines; estimation theory; machine control; observers; oscillations; variable structure systems; closed-loop control; combustion engine test bench; combustion oscillations; disturbed inputs; extended Kalman Filter; high-gain observer; mean quadratic estimation error; noisy measurements; nonlinear extended state observer; sliding-mode observer; Combustion; Engines; Estimation error; Friction; Observers; Output feedback; Performance evaluation; Robust control; Sliding mode control; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2009. ACC '09.
  • Conference_Location
    St. Louis, MO
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4244-4523-3
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2009.5160109
  • Filename
    5160109