Litcius/Paper detail

Aeroelastic Control and Estimation with a Minimal Nonlinear Modal Description

Marc Artola, Norberto Goizueta, Andrew Wynn, Rafael Palacios

2021AIAA Journal24 citationsDOI

Abstract

Modal-based nonlinear moving horizon estimation (MHE) and model predictive control (MPC) strategies for very flexible aeroelastic systems are presented. They are underpinned by an aeroelastic model built from a one-dimensional intrinsic (based on strains and velocities) description of geometrically nonlinear beams and an unsteady vortex lattice aerodynamic model. Construction of a nonlinear modal-based reduced-order model of the aeroelastic system, employing a state-space realization of the linearized aerodynamics around an arbitrary reference point, allows us to capture the main nonlinear geometrical couplings at a very low computational cost. Embedding this model in both MHE and MPC strategies, which solve the system continuous-time adjoints efficiently to compute sensitivities, lays the foundations for real-time estimation and control of highly flexible aeroelastic systems. Finally, the performance and versatility of the framework operating in the nonlinear regime are demonstrated on two very flexible-wing models, with notably different dynamics, and on two different control setups: a gust-load alleviation problem on a very high-aspect-ratio wing with slower dynamics, which involves substantial deflections; and flutter suppression on a flexible wing with significantly faster dynamics, where an unconventional nonlinear stabilization mechanism is unveiled.

Topics & Concepts

AeroelasticityFlutterNonlinear systemAerodynamicsControl theory (sociology)ModalAerodynamic forceFlight control surfacesWingComputational fluid dynamicsComputer scienceEngineeringStructural engineeringPhysicsAerospace engineeringControl (management)Quantum mechanicsChemistryArtificial intelligencePolymer chemistryAeroelasticity and Vibration ControlModel Reduction and Neural NetworksComputational Fluid Dynamics and Aerodynamics