Model predictive and linear quadratic Gaussian control of a wind turbine

Hur, S. and Leithead, W. E. (2016) Model predictive and linear quadratic Gaussian control of a wind turbine. Optimal Control Applications and Methods. ISSN 0143-2087 (https://doi.org/10.1002/oca.2244)

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Abstract

Model predictive and linear quadratic Gaussian controllers are designed for a 5MW variable-speed pitch-regulated wind turbine for three operating points – below rated wind speed, just above rated wind speed, and above rated wind speed. The controllers are designed based on two different linear dynamic models (at each operating point) of the same wind turbine to study the effect of utilising different control design models (i.e. the model used for designing a model-based controller) on the control performance. The performance of the LQG controller is enhanced by improving the robustness, achieved by replacing the Kalman filter with a modified Luenberger observer, whose gain is obtained to minimise the effect of uncertainty and disturbance.

ORCID iDs

Hur, S. ORCID logoORCID: https://orcid.org/0000-0002-9263-1584 and Leithead, W. E.;
  • Item type:Article
    ID code:55448
    Dates:
    Date
    Event
    29 February 2016
    Published
    29 February 2016
    Published Online
    28 January 2016
    Accepted
    Notes:This is the peer reviewed version of the following article: Hur, S., and Leithead, W. E. (2016) Model predictive and linear quadratic Gaussian control of a wind turbine. Optim. Control Appl. Meth., which has been published in final form at http://dx.doi.org/ doi: 10.1002/oca.2244. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
    Subjects:Technology > Engineering (General). Civil engineering (General)
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:03 Feb 2016 15:24
    Last modified:11 Nov 2024 11:19
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/55448
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