Cart (Loading....) | Create Account
Close category search window
 

LPV subspace identification of the edgewise vibrational dynamics of a wind turbine rotor

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Gebraad, P.M.O. ; Delft Center for Syst. & Control, Delft Univ. of Technol., Delft, Netherlands ; van Wingerden, J. ; Fleming, P.A. ; Wright, A.D.

In this paper we apply a state-of-the-art algorithm for subspace identification of linear parameter-varying (LPV) systems to identify the coupled dynamics of the drive-train and the edgewise bending motion of the rotor blades of three-bladed wind turbines. These dynamics are varying with the rotor speed. The identification algorithm uses a factorization which makes it possible to form predictors based on past inputs, outputs, and the known rotor speed. The predictors contain the LPV equivalent of the Markov parameters. Using the predictors, ideas from Predictor Based Subspace IDentification (PBSID) were developed to estimate the state sequence from which the LPV system matrices can be constructed. The algorithm was applied not only to synthetic data generated by a computer simulation of a reference wind turbine, but also to data measured from the CART3 research wind turbine at the National Wind Technology Center of the National Renewable Energy Laboratory (NREL). This paper demonstrates that the linear time-varying behavior of the aeroelastic dynamics of the wind turbine rotor can be captured in an LPV model identified with measured input-output data.

Published in:

Control Applications (CCA), 2011 IEEE International Conference on

Date of Conference:

28-30 Sept. 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.