MURAL - Maynooth University Research Archive Library



    Hierarchical Robust Control of Oscillating Wave Energy Converters With Uncertain Dynamics


    Fusco, Francesco and Ringwood, John (2014) Hierarchical Robust Control of Oscillating Wave Energy Converters With Uncertain Dynamics. IEEE Transactions on Sustainable Energy, 5 (3). ISSN 1949-3029

    [img]
    Preview
    Download (1MB) | Preview


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    Abstract

    Energy-maximizing controllers for wave energy devices are normally based on linear hydrodynamic device models. Such models ignore nonlinear effects which typically manifest themselves for large device motion (typical in this application) and may also include other modeling errors. The effectiveness of a controller is, in general, determined by the match between the model the controller is based on and the actual system dynamics. This match becomes especially critical when the controller is highly tuned to the system. In this paper, we present a methodology for reducing this sensitivity to modeling errors and nonlinear effects by the use of a hierarchical robust controller, which shows small sensitivity to modeling errors, but allows good energy maximization to be recovered through a passivity-based control approach.

    Item Type: Article
    Keywords: Hierarchical robust control; oscillating wave energy converters; uncertain dynamics;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
    Item ID: 6778
    Depositing User: Professor John Ringwood
    Date Deposited: 13 Jan 2016 15:39
    Journal or Publication Title: IEEE Transactions on Sustainable Energy
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Refereed: Yes
    URI:

    Repository Staff Only(login required)

    View Item Item control page

    Downloads

    Downloads per month over past year