Giorgi, Simone, Davidson, Josh, Jakobsen, Morten, 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 |
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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: | 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 |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/14276 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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