Adaptation Strategy for a Distributed Autonomous UAV Formation in Case of Aircraft Loss

TL;DR

This paper presents an adaptation algorithm for distributed UAV formations that maintains stability and performance after the loss of an individual UAV, demonstrated through nonlinear simulation results.

Contribution

The paper introduces a novel adaptation algorithm that reduces interactions among remaining UAVs to preserve formation stability after UAV loss.

Findings

Eliminates increased cruising speed caused by UAV loss

Maintains formation stability through adaptation

Effective in nonlinear UAV models

Abstract

Controlling a distributed autonomous unmanned aerial vehicle (UAV) formation is usually considered in the context of recovering the connectivity graph should a single UAV agent be lost. At the same time, little focus is made on how such loss affects the dynamics of the formation as a system. To compensate for the negative effects, we propose an adaptation algorithm that reduces the increasing interaction between the UAV agents that remain in the formation. This algorithm enables the autonomous system to adjust to the new equilibrium state. The algorithm has been tested by computer simulation on full nonlinear UAV models. Simulation results prove the negative effect (the increased final cruising speed of the formation) to be completely eliminated.