Genest, Romain and Ringwood, John (2016) Receding horizon pseudospectral optimal control for wave energy conversion. In: UKACC 11th International Conference on Control (CONTROL), 2016. IEEE. ISBN 9781467398916

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Abstract

The present study introduces a real-time control algorithm for applications involving energy maximisation and subject to technological limitations. Development of Wave energy converters constitutes an actual topic of research, in their designs and fluid-interactions, and particularly on their controllability. Immersed WECs are subject to fluid-interaction forces, generating unusual solicitations specific to hydrodynamic equation, such as radiation force or excitation forces. Various control strategies were recently developed and more advance control algorithms are currently applied on WECS, such as Model Predictive Control [1], or Pseudospectral optimal control [2]. Such control strategies, capable of maximizing the energy production while insuring the respect of path constraints, are more realistic and applicable in real conditions involving technological limitation aspects. This paper presents a receding horizon type control, based on pseudospectral approach in the control problem resolution. Dealing with irregular waves on a fixed control horizon, the presented control need to work with nonperiodic functions, implying the change of the basis functions involved in the description of the state and control variables, namely the half-range Chebyshev Fourier functions. Application of the receding horizon control is presented for a generic WEC, and compared with a standard MPC algorithm.

Item Type:	Book Section
Additional Information:	This material is based upon works supported by Science Foundation Ireland under Grant No. 13/IA/1886.
Keywords:	wave power plants; Fourier transforms; hydrodynamics; optimal control; predictive control;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
Item ID:	9414
Identification Number:	https://doi.org/10.1109/CONTROL.2016.7737513
Depositing User:	Professor John Ringwood
Date Deposited:	25 Apr 2018 15:25
Publisher:	IEEE
Refereed:	Yes
Funders:	Science Foundation Ireland (SFI)
URI:	Publisher
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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