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    Nonlinear Energy-Maximizing Optimal Control of Wave Energy Systems: A Moment-Based Approach


    Faedo, Nicolas and Scarciotti, Giordano and Astolfi, Alessandro and Ringwood, John (2021) Nonlinear Energy-Maximizing Optimal Control of Wave Energy Systems: A Moment-Based Approach. IEEE Transactions on Control Systems Technology, 29 (6). pp. 2533-2547. ISSN 1063-6536

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    Abstract

    Linear dynamics are virtually always assumed when designing optimal controllers for wave energy converters (WECs), motivated by both their simplicity and computational convenience. Nevertheless, unlike traditional tracking control applications, the assumptions under which the linearization of WEC models is performed are challenged by the energy-maximizing controller itself, which intrinsically enhances device motion to maximize power extraction from incoming ocean waves. In this article, we present a moment-based energy-maximizing control strategy for WECs subject to nonlinear dynamics. We develop a framework under which the objective function (and system variables) can be mapped to a finite-dimensional tractable nonlinear program, which can be efficiently solved using state of-the-art nonlinear programming solvers. Moreover, we show that the objective function belongs to a class of generalized convex functions when mapped to the moment domain, guaranteeing the existence of a global energy-maximizing solution and giving explicit conditions for when a local solution is, effectively, a global maximizer. The performance of the strategy is demonstrated through a case study, where we consider (state and input-constrained) energy maximization for a state-of-the art CorPower-like WEC, subject to different hydrodynamic nonlinearities.

    Item Type: Article
    Keywords: Energy maximization; moment; moment matching; nonlinear optimal control; wave energy;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
    Item ID: 16123
    Identification Number: https://doi.org/10.1109/TCST.2020.3047229
    Depositing User: Professor John Ringwood
    Date Deposited: 16 Jun 2022 14:29
    Journal or Publication Title: IEEE Transactions on Control Systems Technology
    Refereed: Yes
    URI:

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