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    Receding Horizon Pseudospectral Control for Energy Maximization With Application to Wave Energy Devices


    Genest, Romain and Ringwood, John (2017) Receding Horizon Pseudospectral Control for Energy Maximization With Application to Wave Energy Devices. IEEE Transactions on Control Systems Technology, 25 (1). pp. 29-38. ISSN 1063-6536

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    Abstract

    This paper addresses the issue of real-time control for applications, subject to physical constraints, involving an energy maximization objective. Typical application areas include renewable energy systems where, in spite of the fact that the raw energy resource is free, the capital and operational costs associated with the energy conversion process are not. In addition, economic energy delivery can only be achieved if the conversion device is operated efficiently. Previous approaches to this problem include model predictive control (MPC), but the computational cost associated with MPC can be high. Pseudospectral solutions show considerable promise in achieving a good balance between performance and computation, but currently available solutions deal with fixed-period optimization. In this paper, a receding horizon real-time pseudospectral control is developed, based on half-range Chebyshev Fourier basis functions, which can accurately represent harmonic signals in the application domain, while also efficiently dealing with the signal truncation effects associated with a receding horizon formulation. An application example, based on a wave energy converter, is used to illustrate the new control algorithm.
    Item Type: Article
    Additional Information: Cite as: Genest, R. & Ringwood, J. 2017, "Receding Horizon Pseudospectral Control for Energy Maximization With Application to Wave Energy Devices", .
    Keywords: Optimal control; pseudospectral method; receding horizon; 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: 11779
    Identification Number: 10.1109/TCST.2016.2554524
    Depositing User: Professor John Ringwood
    Date Deposited: 20 Nov 2019 17:38
    Journal or Publication Title: IEEE Transactions on Control Systems Technology
    Publisher: IEEE
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/11779
    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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