Data-driven unsteady aeroelastic modeling for control

TL;DR

This paper develops low-order, data-driven models for unsteady aeroelastic forces and deformation in flexible wings, enabling real-time control and maneuver tracking with constraints.

Contribution

It extends existing unsteady aerodynamic models to include flexible wing deformation, providing accurate, low-dimensional models for control applications.

Findings

Models successfully track aggressive maneuvers

Models constrain maximum wing deformation

Effective for low Reynolds number flows

Abstract

Aeroelastic structures, from insect wings to wind turbine blades, experience transient unsteady aerodynamic loads that are coupled to their motion. Effective real-time control of flexible structures relies on accurate and efficient predictions of both the unsteady aeroelastic forces and airfoil deformation. For rigid wings, classical unsteady aerodynamic models have recently been reformulated in state-space for control and extended to include viscous effects. Here we further extend this modeling framework to include the deformation of a flexible wing in addition to the quasi-steady, added mass, and unsteady viscous forces. We develop low-order linear models based on data from direct numerical simulations of flow past a flexible wing at low Reynolds number. We demonstrate the effectiveness of these models to track aggressive maneuvers with model predictive control while constraining maximum wing deformation. This system identification approach provides an interpretable, accurate, and low-dimensional representation of an aeroelastic system that can aid in system and controller design for applications where transients play an important role.