Giorgi, Simone, Davidson, Josh and Ringwood, John (2016) Identification of Wave Energy Device Models From Numerical Wave Tank Data—Part 2: Data-Based Model Determination. IEEE Transactions on Sustainable Energy, 7 (3). pp. 1020-1027. ISSN 1949-3029
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Abstract
In this paper and its companion, the identification of mathematical models describing the behaviour of wave energy devices (WECs) in the ocean is investigated through the use of numerical wave tank experiments. When the wave amplitude and the WEC displacement are not negligible with respect to the WEC dimensions, nonlinear hydrodynamic effects may appear, and the accuracy of linear hydrodynamic models is reduced, leading to the necessity of introducing some nonlinearities in the model structure. This paper proposes, for WEC modelling, the use of discrete-time nonlinear autoregressive with exogenous input (NARX) models, as an alternative to continuous-time models. Techniques of model identification are also explained and applied to a case study.
Item Type: | Article |
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Additional Information: | This work was supported in part by the Enterprise Ireland under Grant EI/CF/2011/1320, in part by the Irish Government and the European Union under Ireland’s EU Structural and Investment Funds Programme 2014-2020, and in part by the Science Foundation Ireland under Grant 13/IA/1886. Paper no. TSTE-00635-2015. |
Keywords: | System identification; numerical wave tank; wave energy; discrete-time modelling; NARX model; ARX model; artificial neural network; 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: | 9399 |
Identification Number: | 10.1109/TSTE.2016.2515500 |
Depositing User: | Professor John Ringwood |
Date Deposited: | 23 Apr 2018 16:20 |
Journal or Publication Title: | IEEE Transactions on Sustainable Energy |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Funders: | Enterprise Ireland (EI), European Structural and Investment Funds Programme, Science Foundation Ireland (SFI) |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/9399 |
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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