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Control of the archimedes wave swing using neural networks

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This paper addresses the control of the Archimedes Wave Swing, a fully-submerged Wave Energy Converter (WEC), of which a prototype has already been built and tested. Simulation results are presented in which Internal Model Control (IMC) is used, both with linear models and with non-linear neural network (NN) models. To the best of our knowledge this is the first time NN-based control is being applied to design a controller for a WEC. NNs are a mathematical tool suitable to model the behaviour of dynamic systems, both linear and non-linear (as in our case). Significant absorbed wave energy increases were found, both using linear models and NNs. Results were better when IMC with NNs was employed (with a nearly sixfold increase against a fivefold increase), except for the May—September period, when IMC with linear models performs better.

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Neural networks Wave energy Internal Model Control Archimedes wave swing Control

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Citation

BEIRÃO, Pedro; [et al] – Control of the archimedes wave swing using neural networks. In Proceedings of the 7th European Wave and Tidal Energy Conference (EWTEC 2007). Porto, Portugal: Fundação Eng. António de Almeida, 2007. Pp. 1-10

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Fundação Eng. António de Almeida

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