A Model Free Control Based on Machine Learning for Energy Converters in an Array

A Model Free Control Based on Machine Learning for Energy Converters in an Array

This paper introduces a machine learning based control strategy for energy converter arrays designed to work under realistic conditions where the optimal control parameter can not be obtained analytically. The control strategy neither relies on a mathematical model, nor does it need a priori informa...

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Bibliographic Details
Main Authors: Simon Thomas, Marianna Giassi, Mikael Eriksson, Malin Göteman, Jan Isberg, Edward Ransley, Martyn Hann, Jens Engström
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Big Data and Cognitive Computing
Subjects:
machine learning
wave energy
power take-off
artificial neural network
wave tank test
physical scale model
floating point absorber
damping
control
collaborative
Online Access:https://www.mdpi.com/2504-2289/2/4/36

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