Experiences of system identification applied to ship steering☆
References (24)
- et al.
Identification of ship steering dynamics
Automatica
(1976) - et al.
Adaptive autopilots for tankers
Automatica
(1979) Lectures on ship hydrodynamics, steering and maneuverability
Use of an information theoretic quantity for statistical model identification
- et al.
Numerical identification of linear dynamic systems from normal operating records
- et al.
Application of system identification techniques to the determination of ship dynamics
- et al.
The identification of linear ship steering dynamics using maximum likelihood parameter estimation
- et al.
Large tankers—wind coefficients and speed loss due to wind and sea
Trans. R. Inst. Naval Architects
(1974) - et al.
System identification of linear and non-linear ship steering dynamics
- et al.
Planar motion mechanism tests and full-scale steering and manoeuvring predictions for a Mariner class vessel
Theory of the flight of airplanes in isotropic turbulence; review and extension
Cited by (79)
Black-box modeling of ship maneuvering motion based on multi-output nu-support vector regression with random excitation signal
2022, Ocean EngineeringCitation Excerpt :The data collection can be performed repeatedly when needed, even when the vessel is on its daily voyage. As for the identification algorithm, many techniques have been successfully applied, such as maximum likelihood estimate (Källström and Åström, 1981), model reference approach (Van Amerongen, 1984), extended Kalman filter (Perera et al., 2011), genetic algorithm (Sutulo and Guedes Soares, 2014), least squares method (Wang et al., 2020a), Neural Network (NN) (Zhang and Zou, 2013) and Support Vector Machines (SVM) (Luo and Zou, 2009). Among them, SVM algorithm has a strict theoretical foundation following the principle of structural risk minimization.
Recurrent neural networks for nonparametric modeling of ship maneuvering motion
2022, International Journal of Naval Architecture and Ocean EngineeringModeling, parameter identification, guidance and control of an unmanned surface vehicle with experimental results
2021, Ocean EngineeringCitation Excerpt :In (AAströmet and Källström, 1976), a new frequency domain system identification method for estimation of hydrodynamic derivatives embedded in linear steering equations for ship maneuvering in calm seas is presented. In (Källströmet and \AAström, 1981), the authors determine the parameter of a linear continuous time model using discrete time measurements. In (Rajeshet and Bhattacharyya, 2008), The authors summarize the experiences obtained from applying system identification methods to many different ships.
Identification of coupled response models for ship steering and roll motion using support vector machines
2021, Applied Ocean Research
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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.