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Nonlinear Model Reduction for Aeroelastic Systems: Control Framework and Implementation

This study presents a comprehensive framework for the control of flexible nonlinear aeroelastic systems. It focuses on model reduction techniques that decrease the dimensionality and computational cost associated with the full-order model (FOM). The approach encompasses the development of a reduced-order model (ROM) by leveraging slow aeroelastic eigenmodes, transformation of coordinates, and the inclusion of higher-order effects. The research also examines the interaction of rigid body dynamics and aerodynamic models, with specific examples including linear and nonlinear flutter dynamics, gust responses, and control laws applied to aerofoil sections and wings.

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Nonlinear Model Reduction for Aeroelastic Systems: Control Framework and Implementation

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  1. Nonlinear Model Reduction of an Aeroelastic System A. DaRonch and K.J. Badcock University of Liverpool, UK Bristol, 20 October 2011

  2. Objective Framework for control of a flexible nonlinear aeroelastic system Rigid body dynamics CFD for realistic predictions Model reduction to reduce size and cost of the FOM Design of a control law to close the loop

  3. Full-Order Model Aeroelastic system in the form of ODEs • Large dimension • Expensive to solve in routine manner • Independent parameter, U* (altitude, density)

  4. Taylor Series Equilibrium point, w0 • Expand residual in a Taylor series • Manipulable control, uc, and external disturbance, ud

  5. Generalized Eigenvalue Problem Calculate right/left eigensolutions of the Jacobian, A(w’) • Biorthogonality conditions • Small number of eigenvectors, m<n

  6. Model Reduction Project the FOM onto a small basis of aeroelasticeigenmodes (slow modes) • Transformation of coordinates FOM to ROM where m<n

  7. Linear Reduced-Order Model Linear dynamics of FOM around w0 From the transformation of coordinates, a linear ROM

  8. Nonlinear Reduced-Order Model Include higher order terms in the FOM residual B involves ~m2Jacobian evaluations, while C~m3. Look at the documentation

  9. Governing Equations FE matrices for structure Linear potential flow (Wagner, Küssner), convolution IDEs to ODEs by introducing aerodynamic states

  10. State Space Form

  11. Procedure FOM • Time-integration ROM • Right/left eigensolution of Jacobian, A(w’) • Transformation of coordinates w’ to z • Form ROM terms: matrix-free product for Jacobian evaluations • Time-integration of a small system

  12. Examples Aerofoil section • nonlinear struct + linear potential flow Wing model • nonlinear struct + linear potential flow Wing model • nonlinear struct + CFD

  13. Aerofoil Section

  14. Aerofoil Section 2 dof structural model • Flap for control • Gust perturbation Nonlinear restoring forces Gust as external disturbance (not part of the problem)

  15. AeroelasticEigenvalues at 0.95 of linear flutter speed

  16. FOM/ROM gust response – linear structural model

  17. FOM gust response – linear/nonlinear structural model

  18. FOM/ROM gust response – nonlinear structural model

  19. Wing model Slender wing with aileron 20 states per node

  20. Wing model Linear flutter speed: 13m/s First bending: 7.0Hz Highest modes: 106Hz For time integration of FOM: dt~10-7 ROM with few slow aeroelastic modes: dt~10-2

  21. Gust disturbance at 0.01 of linear flutter speed

  22. Gust disturbance at 0.99 of linear flutter speed

  23. Ongoing work Control problem for linear aerofoil section: apply control law to the FOM Same iteration for a wing model Include rigid body dynamics and test model reduction Extend aerodynamic models to CFD

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