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    Identification of dynamic models for a wave energy converter from experimental data


    Giorgi, Simone and Davidson, Josh and Jakobsen, Morten and Kramer, Morten and Ringwood, John (2019) Identification of dynamic models for a wave energy converter from experimental data. Ocean Engineering, 183. pp. 426-436. ISSN 0029-8018

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    Abstract

    This paper addresses the issue of hydrodynamic model identification from recorded tank test data, for a prototype wave energy device. The study focusses on nonlinear Kolmogorov–Gabor polynomial models, with linear models also used as a baseline reference. Six different experimental data sets are employed for model identification and validation, all derived from a JONSWAP input sea state. Compared to identification on numerical data, this study shows that the determination of model structure and orders is not so straightforward, but that consistent and useful computationally efficient models can be obtained. For the particular tests undertaken, in which the prototype device generally behaves as a wave follower, the nonlinear models only show very marginal performance improvement over the linear ones.

    Item Type: Article
    Additional Information: Funding: This paper is based upon work supported by Science Foundation Ireland [Grant No. 13/IA/1886] and by Enterprise Ireland [Grant EI/CF/2011/1320]. Cite as: Simone Giorgi, Josh Davidson, Morten Jakobsen, Morten Kramer, John V. Ringwood, Identification of dynamic models for a wave energy converter from experimental data, Ocean Engineering, Volume 183, 2019, Pages 426-436, ISSN 0029-8018, https://doi.org/10.1016/j.oceaneng.2019.05.008.
    Keywords: Wave energy; System identification; Wave tank test; Discrete-time modelling; Nonlinear; NARX model; ARX model; Kolmogorov–Gabor polynomial model;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
    Item ID: 14276
    Identification Number: https://doi.org/10.1016/j.oceaneng.2019.05.008
    Depositing User: Professor John Ringwood
    Date Deposited: 29 Mar 2021 16:15
    Journal or Publication Title: Ocean Engineering
    Publisher: Elsevier
    Refereed: Yes
    URI:

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