Scheduled Model Predictive Control of a Wind Tur bine

Through high order aeroelastic simulations in turbulent wind, it has been shown that a Scheduled Model Predictive Controller (SMPC) can successfully control a wind turbine in above rated wind conditions. The SMPC shows the ability to control Multi-Input MultiOutput systems with multiple control objectives, allow for system input constraints and also adjust to the aerodynamic nonlinearities of the turbine system. The implementation of the SMPC is also only as complex as implementing a Linear Model Predictive Controller (LMPC) but provides the benefits of being able to control nonlinear systems with higher performance. Furthermore it has been shown that by using a SMPC the user has the ability to finely tune each controller the SMPC is comprised of giving more tailored performance to various operating regions.

[1]  Nikolaos Kazantzis,et al.  Control-Relevant Discretization of Nonlinear Systems With Time-Delay Using Taylor-Lie Series , 2005 .

[2]  Kathryn E. Johnson,et al.  Baseline Results and Future Plans for the NREL Controls Advanced Research Turbine: Preprint , 2003 .

[3]  Ervin Bossanyi,et al.  The Design of closed loop controllers for wind turbines , 2000 .

[4]  William Leithead,et al.  Appropriate realization of gain-scheduled controllers with application to wind turbine regulation , 1996 .

[5]  G. Irwin,et al.  Nonlinear model based predictive control using multiple local models , 2001 .

[6]  M. L. Buhl,et al.  TurbSim User's Guide: Revised February 2007 for Version 1.21 , 2007 .

[7]  James B. Rawlings,et al.  Tutorial overview of model predictive control , 2000 .

[8]  Richard A. Santos Damage mitigating control for wind turbines , 2007 .

[9]  Jason Jonkman,et al.  FAST User's Guide , 2005 .

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

[11]  B. Jonkman Turbsim User's Guide: Version 1.50 , 2009 .

[12]  Carlo L. Bottasso,et al.  Performance comparison of control schemes for variable-speed wind turbines , 2007 .

[13]  Mark J. Balas,et al.  Testing State-Space Controls for the Controls Advanced Research Turbine: Preprint , 2006 .

[14]  Doug Cooper,et al.  A Practical Multiple Model Adaptive Strategy for Multivariable Model Predictive Control , 2003 .

[15]  B. Jonkman,et al.  TurbSim User's Guide , 2005 .

[16]  James B. Rawlings,et al.  Model predictive control with linear models , 1993 .

[17]  A. D. Wright,et al.  Modern Control Design for Flexible Wind Turbines , 2004 .

[18]  Lars Christian Henriksen,et al.  Model Predictive Control of a Wind Turbine , 2007 .

[19]  O. Curea,et al.  LPV Control of Wind Turbines for Fatigue Loads Reduction using Intelligent Micro Sensors , 2007, 2007 American Control Conference.

[20]  Sven Creutz Thomsen Nonlinear Control of a Wind Turbine , 2006 .

[21]  K. A. Stol,et al.  Wind Turbine Field Testing of State-Space Control Designs: August 25, 2003--November 30, 2003 , 2004 .

[22]  James B. Rawlings,et al.  Constrained linear quadratic regulation , 1998, IEEE Trans. Autom. Control..

[23]  Karl Stol,et al.  Simulating MIMO Feedback Linearization Control of Wind Turbines Using FAST , 2008 .

[24]  Kathryn E. Johnson,et al.  METHODS FOR INCREASING REGION 2 POWER CAPTURE ON A VARIABLE SPEED HAWT , 2004 .