This paper deals with the identification of linear discrete-time multivariable models of an autonomous underwater vehicle (AUV). The observer Kaiman filter identification (OKID) method is applied with the main objective of evaluating its effectiveness to the experimental identification of the dynamic behaviour of an AUV. After presenting the mathematical background of the OKID algorithm, the proposed method is first validated on the basis of simulated data of both the linearized and nonlinear yaw dynamics of an AUV. Subsequently, the identification algorithm is applied to a set of experimental data. Results suggest that the method can be an efficient tool for the experimental identification of AUV dynamics.


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    Title :

    Observer Kalman filter identification of an autonomous underwater vehicle


    Additional title:

    Kalman-Filter-Identifikation des Beobachters für ein autonomes Unterwasserfahrzeug


    Contributors:
    Tiano, A. (author) / Sutton, R. (author) / Lozowicki, A. (author) / Naeem, W. (author)


    Publication date :

    2007


    Size :

    13 Seiten, 17 Bilder, 4 Tabellen, 11 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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