• DocumentCode
    1716487
  • Title

    Application of LS and EKF techniques to the identification of underwater vehicles

  • Author

    Alessandri, A. ; Caccia, M. ; Indiveri, G. ; Veruggio, G.

  • Author_Institution
    Naval Autom. Inst., Geneva, Italy
  • Volume
    2
  • fYear
    1998
  • Firstpage
    1084
  • Abstract
    The modelling and identification of an open-frame underwater vehicle for marine applications is considered. The goal of this work is to demonstrate that modelling and identification of small underwater vehicles is feasible at low cost: the identification has been accomplished using only standard on-board devices. First, the selection of a model for such vehicles is discussed, as well as a suitable identification method. The parameters of the selected model are identified in two steps: based on least squares (LS) and extended Kalman filter (EKF) techniques. The results of the identification applied to experimental data are presented and discussed
  • Keywords
    Kalman filters; dynamics; identification; least squares approximations; modelling; underwater vehicles; dynamics; extended Kalman filter; identification; least squares method; modelling; underwater vehicles; Application software; Fluid dynamics; Marine vehicles; Navier-Stokes equations; Nonlinear equations; Parameter estimation; Power system modeling; Remotely operated vehicles; Underwater vehicles; Vehicle dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications, 1998. Proceedings of the 1998 IEEE International Conference on
  • Conference_Location
    Trieste
  • Print_ISBN
    0-7803-4104-X
  • Type

    conf

  • DOI
    10.1109/CCA.1998.721624
  • Filename
    721624