Control of the archimedes wave swing using neural networks - Beirão, Pedro (2019)
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.