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    Towards realistic non-linear receding-horizon spectral control of wave energy converters


    Mérigaud, Alexis and Ringwood, John (2018) Towards realistic non-linear receding-horizon spectral control of wave energy converters. Control Engineering Practice, 81. pp. 145-161. ISSN 0967-0661

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    Abstract

    Non-linear, power-maximising control of wave energy converters (WECs) can be achieved within a receding-horizon control framework, whereby an upper loop calculates a reference trajectory in real-time, ensuring maximal power absorption under operational constraints, while a tracking loop drives the device along the generated trajectory. This paper articulates the four fundamental components of such a control strategy: reference generation calculations, tracking loop, and wave excitation estimation and forecasting. The upper-loop optimisation problem is efficiently solved through a Fourier spectral method, taking into account non-linear dynamics and constraints. Tracking is achieved through a linear state feedback, combined with a non-linear feed-forward term. An extended Kalman filter is used for excitation force estimation, based on noisy WEC position and acceleration measurements. Finally, wave excitation forecasts are based on a linear predictor, whose coefficients are derived from the wave spectrum (on a sea-state-by-sea-state basis). The practical issues and trade-offs, which arise when the four components listed above are combined within a practical implementation, are investigated by means of realistic numerical simulations, using a WEC model comprising a combination of static and velocity-dependent non-linear forces.

    Item Type: Article
    Additional Information: This paper is based upon work supported by Science Foundation Ireland under Grant No. 12/RC/2302 for the Marine Renewable Ireland (MaREI) centre.
    Keywords: Wave energy converters; Power maximisation; Optimal control; Receding-horizon control; Fourier spectral control; Constraints; Non-linear systems; Trajectory tracking; Extended Kalman filter; Measurement noise; Gaussian process;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
    Item ID: 12545
    Identification Number: https://doi.org/10.1016/j.conengprac.2018.08.024
    Depositing User: Professor John Ringwood
    Date Deposited: 05 Mar 2020 15:38
    Journal or Publication Title: Control Engineering Practice
    Publisher: Elsevier
    Refereed: Yes
    Funders: Science Foundation Ireland (SFI), Marine Renewable Ireland Centre
    URI:

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