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Model predictive and linear quadratic Gaussian control of a wind turbine
Author(s) -
Hur S.,
Leithead W. E.
Publication year - 2016
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2244
Subject(s) - linear quadratic gaussian control , control theory (sociology) , turbine , kalman filter , wind speed , model predictive control , robustness (evolution) , gaussian , observer (physics) , engineering , computer science , control engineering , optimal control , mathematics , control (management) , mathematical optimization , mechanical engineering , biochemistry , chemistry , physics , quantum mechanics , artificial intelligence , meteorology , gene
Summary 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. Copyright © 2016 John Wiley & Sons, Ltd.