LPV Identification of Wind Turbine Rotor Vibrational Dynamics Using Periodic Disturbance Basis Functions

This brief presents an identification experiment performed on the coupled dynamics of the edgewise bending vibrations of the rotor blades and the in-plane motion of the drivetrain of three-bladed wind turbines. These dynamics vary with rotor speed, and are subject to periodic wind flow disturbances. This brief demonstrates that this time-varying behavior can be captured in a linear parameter-varying (LPV) model with the rotor speed as the scheduling signal, and with additional sinusoidal inputs that are used as basis functions for the periodic wind flow disturbances. By including these inputs, the predictor-based LPV subspace identification approach (LPV PBSIDopt) was tailored for wind turbine applications. Using this tailor-made approach, the LPV model is identified from data measured with the three-bladed Controls Advanced Research Turbine (CART3) at the National Renewable Energy Laboratory's National Wind Technology Center.

[1]  Paul Fleming,et al.  Resonant Vibrations Resulting from the Re-Engineering of a Constant-Speed 2-Bladed Turbine to a Variable-Speed 3-Bladed Turbine , 2010 .

[2]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[3]  Michel Verhaegen,et al.  Subspace identification of Bilinear and LPV systems for open- and closed-loop data , 2009, Autom..

[4]  J. W. Van Wingerden,et al.  Control of wind turbines with 'Smart' rotors : Proof of concept & LPV subspace identification , 2008 .

[5]  Michel Verhaegen,et al.  Closed‐loop identification of the time‐varying dynamics of variable‐speed wind turbines , 2009 .

[6]  A. Packard,et al.  Robust performance of linear parametrically varying systems using parametrically-dependent linear feedback , 1994 .

[7]  Morten Hartvig Hansen,et al.  Aeroelastic instability problems for wind turbines , 2007 .

[8]  P. Apkarian,et al.  Advanced gain-scheduling techniques for uncertain systems , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[9]  G. Bir.  Multi-Blade Coordinate Transformation and its Application to Wind Turbine Analysis , 2008 .

[10]  Michael Athans,et al.  Guaranteed properties of gain scheduled control for linear parameter-varying plants , 1991, Autom..

[11]  Fernando D. Bianchi,et al.  Wind Turbine Control Systems: Principles, Modelling and Gain Scheduling Design , 2006 .

[12]  Jan-Willem van Wingerden,et al.  LPV subspace identification of the edgewise vibrational dynamics of a wind turbine rotor , 2011, 2011 IEEE International Conference on Control Applications (CCA).

[13]  Marco Lovera,et al.  LPV/LFT modelling and identification: overview, synergies and a case study , 2008, 2008 IEEE International Conference on Computer-Aided Control Systems.

[14]  Kathryn E. Johnson,et al.  Development, implementation, and testing of fault detection strategies on the National Wind Technology Center’s controls advanced research turbines , 2011 .

[15]  J. W. van Wingerden,et al.  Sparse Estimation for Predictor-Based Subspace Identification of LPV Systems , 2012 .

[16]  Michel Verhaegen,et al.  LPV identification of an aeroelastic flutter model , 2010, 49th IEEE Conference on Decision and Control (CDC).

[17]  Vincent Verdult,et al.  Kernel methods for subspace identification of multivariable LPV and bilinear systems , 2005, Autom..

[18]  Michel Verhaegen,et al.  Closed-loop system identification of wind turbines in the presence of periodic effects , 2010 .

[19]  Jakob Stoustrup,et al.  Linear parameter varying control of wind turbines covering both partial load and full load conditions , 2009 .

[20]  M. Verhaegen,et al.  LPV subspace identification using a novel nuclear norm regularization method , 2011, Proceedings of the 2011 American Control Conference.