Non-parametric dynamic system identification of ships using multi-output gaussian processes
Files
(Published version)
Date
2018
Authors
Ramirez, W.A.
Leong, Z.Q.
Nguyen, H.
Jayasinghe, S.G.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Ocean Engineering, 2018; 166:26-36
Statement of Responsibility
Conference Name
Abstract
A novel application of non-parametric system identification algorithm for a surface ship has been employ on this study with the aim of modelling ships dynamics with low quantity of data. The algorithm is based on multi-output Gaussian processes and its ability to model the dynamic system of a ship without losing the relationships between coupled outputs is explored. Data obtained from the simulation of a parametric model of a container ship is used for the training and validation of the multi-output Gaussian processes. The required methodology and metric to implement Gaussian processes for a 4 degrees of freedom (DoF) ship is also presented in this paper. Results show that multi-output Gaussian processes can be accurately applied for non-parametric dynamic system identification in ships with highly coupled DoF.
School/Discipline
Dissertation Note
Provenance
Description
Access Status
Rights
Copyright 2018 Elsevier
Access Condition Notes: Accepted manuscript is available open access