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Non-parametric dynamic system identification of ships using multi-output Gaussian Processes


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Ariza Ramirez, W, Leong, ZQ ORCID: 0000-0002-0644-1822, Nguyen, H ORCID: 0000-0003-0118-8597 and Jayasinghe, SG ORCID: 0000-0002-3304-9455 2018 , 'Non-parametric dynamic system identification of ships using multi-output Gaussian Processes' , Ocean Engineering, vol. 166 , pp. 26-36 , doi: 10.1016/j.oceaneng.2018.07.056.

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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.

Item Type: Article
Authors/Creators:Ariza Ramirez, W and Leong, ZQ and Nguyen, H and Jayasinghe, SG
Keywords: dependent Gaussian processes, dynamic system identification, multi-output Gaussian processes, non-parametric identification, oceanic vehicles
Journal or Publication Title: Ocean Engineering
Publisher: Pergamon-Elsevier Science Ltd
ISSN: 0029-8018
DOI / ID Number: 10.1016/j.oceaneng.2018.07.056
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© 2018 Elsevier Ltd. All rights reserved

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