Modeling and Controls of Fluid-Structure Interactions (FSI) in Dynamic Morphing Flight

TL;DR

This work addresses the challenge of predicting and controlling fluid-structure interactions in a dynamic morphing-wing drone by extending an unsteady FSI model for Aerobat to banking turns using a Kinova arm. The authors derive a Wagner-function–based lift dynamic within a lifting-line framework, calibrate it with force-moment measurements, and implement a collocation-based controller to achieve 3D path tracking in simulation. Key contributions include a test platform for tuning the FSI model, experimental force-moment data for validation, and a collocation optimization approach enabling closed-loop 3D maneuver tracking. The findings demonstrate improved prediction of complex 3D maneuvers and highlight the potential for practical closed-loop control of morphing-wing drones in flight.

Abstract

The primary aim of this study is to enhance the accuracy of our aerodynamic Fluid-Structure Interaction (FSI) model to support the controlled tracking of 3D flight trajectories by Aerobat, which is a dynamic morphing winged drone. Building upon our previously documented Unsteady Aerodynamic model rooted in horseshoe vortices, we introduce a new iteration of Aerobat, labeled as version beta, which is designed for attachment to a Kinova arm. Through a series of experiments, we gather force-moment data from the robotic arm attachment and utilize it to fine-tune our unsteady model for banking turn maneuvers. Subsequently, we employ the tuned FSI model alongside a collocation control strategy to accomplish 3D banking turns of Aerobat within simulation environments. The primary contribution lies in presenting a methodical approach to calibrate our FSI model to predict complex 3D maneuvers and successfully assessing the model's potential for closed-loop flight control of Aerobat using an optimization-based collocation method.

Figures (6)

• Figure 1: Shows Northeastern University Aerobat platform designed to inspect dynamic morphing wing flight
• Figure 2: (a) Shows the test setup, including the arm, load-cell, Aerobat version $\beta$, and data acquisition system. (b) Snapshots of arm and Aerobat during the constrained banking turn at different sample times are overlaid and illustrated in this image.
• Figure 3: Illustrates comparison of the force-moment trajectories between experiment and simulation.
• Figure 4: Illustrates wake structures (iso-metric view) and vorticity plots in the frontal plane of flapping at (i) the beginning of downstroke, (ii) middle of downstroke, (iii) beginning of upstroke, and (iv) the middle of upstroke during banking turn.
• Figure 5: Shows all of Aerobat state trajectories including body orientation, position, and body angles (shoulder and elbow joints).