System identification of Vessel Manoeuvring Models
Journal article, 2022

Identifying the ship’s maneuvering dynamics can build models for ship maneuverability predictions with a wide range of useful applications. A majority of the publications in this field are based on simulated data. In this paper model test data is used. The identification process can be decomposed into finding a suitable manoeuvring model for the hydrodynamic forces and to correctly handle errors from the measurement noise. A parameter estimation is proposed to identify the hydrodynamic derivatives. The most suitable manoeuvring model is found using the parameter estimation with cross-validation on a set of competing manoeuvring models. The parameter estimation uses inverse dynamics regression and Extended Kalman filter (EKF) with a Rauch Tung Striebel (RTS) smoother. Two case study vessels, wPCC and KVLCC2, with very different maneuverability characteristics are used to demonstrate and validate the proposed method. Turning circle predictions with the robust manoeuvring models, trained on zigzag model tests, show good agreement with the corresponding model test results for both ships.

Ship manoeuvring

Inverse dynamics

RTS smoother

Multicollinearity

System identification

Extended Kalman filter

Author

Martin Alexandersson

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Wengang Mao

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Jonas Ringsberg

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Ocean Engineering

0029-8018 (ISSN)

Vol. 266 1 1-17 112940

DEMOPS - Machine learning based speed-power performance modelling to reduce fuel cost and emissions from shipping

Lighthouse, 2020-01-01 -- 2022-12-31.

Swedish Transport Administration, 2020-01-01 -- 2024-12-31.

Swedish Transport Administration, 2020-01-01 -- 2022-12-31.

Driving Forces

Sustainable development

Areas of Advance

Transport

Roots

Basic sciences

Subject Categories

Vehicle Engineering

Oceanography, Hydrology, Water Resources

Probability Theory and Statistics

DOI

10.1016/j.oceaneng.2022.112940

Related datasets

wPCC manoeuvring model tests [dataset]

DOI: 10.17632/j5zdrhr9bf.2 URI: https://data.mendeley.com/datasets/j5zdrhr9bf/2

More information

Latest update

1/23/2023