Elsevier

Automatica

Volume 17, Issue 1, January 1981, Pages 187-198
Automatica

Experiences of system identification applied to ship steering

https://doi.org/10.1016/0005-1098(81)90094-7Get rights and content

Abstract

Different system identification methods have been applied to determine ship steering dynamics from full-scale experiments. The techniques used include output error, maximum likelihood and more general prediction error methods. Different model structures have been investigated ranging from input-output models in difference equation form to the equations of motion in their natural form. Effects of disturbances, errors and dynamics in sensors and actuators have been considered. Programs for interactive system identification have been used extensively. The experiments have been performed both under open loop and closed loop conditions. Both linear and nonlinear models have been considered. The paper summarizes the experiences obtained from applying system identification methods to many different ships. The results have been applied both to investigate steering properties and to design autopilots for ship steering. Insight into ship steering dynamics and identification methodology has been obtained.

References (24)

  • K.J. Ȧström et al.

    Identification of ship steering dynamics

    Automatica

    (1976)
  • C.G. Källström et al.

    Adaptive autopilots for tankers

    Automatica

    (1979)
  • M.A. Abkowitz

    Lectures on ship hydrodynamics, steering and maneuverability

  • H. Akaike

    Use of an information theoretic quantity for statistical model identification

  • K.J. Ȧström et al.

    Numerical identification of linear dynamic systems from normal operating records

  • K.J. Ȧström et al.

    Application of system identification techniques to the determination of ship dynamics

  • K.J. Ȧström et al.

    The identification of linear ship steering dynamics using maximum likelihood parameter estimation

  • W.B. van Berlekom et al.

    Large tankers—wind coefficients and speed loss due to wind and sea

    Trans. R. Inst. Naval Architects

    (1974)
  • L. Byström et al.

    System identification of linear and non-linear ship steering dynamics

  • M.S. Chislett et al.

    Planar motion mechanism tests and full-scale steering and manoeuvring predictions for a Mariner class vessel

  • B. Etkin

    Theory of the flight of airplanes in isotropic turbulence; review and extension

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    The original version of this paper was presented at the 5th IFAC Symposium on Identification and System Parameter Estimation which was held in Darmstadt, Federal Republic of Germany during September 1979. The published Proceedings of this IFAC Meeting may be ordered from: Pergamon Press Limited, Headington Hill Hall, Oxford OX3 0BW, England. This paper was recommended for publication in revised form by associate editor R. Isermann.

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