Terminal Iterative Learning Control for Autonomous Aerial Refueling under Aerodynamic Disturbances

TL;DR

This paper introduces a terminal iterative learning control method for autonomous aerial refueling that effectively compensates for aerodynamic disturbances, ensuring accurate docking despite environmental challenges.

Contribution

It proposes a novel terminal iterative learning control approach integrated with autopilot systems for improved aerial refueling docking accuracy under disturbances.

Findings

Fast learning speed in simulations

Successful docking under aerodynamic disturbances

Effective compensation for bow wave effects

Abstract

This paper studies the model of the probe-drogue aerial refueling system under aerodynamic disturbances, and proposes a docking control method based on terminal iterative learning control to compensate for the docking errors caused by aerodynamic disturbances. The designed controller works as an additional unit for the trajectory generation function of the original autopilot system. Simulations based on our previously published simulation environment show that the proposed control method has a fast learning speed to achieve a successful docking control under aerodynamic disturbances including the bow wave effect.