Adaptive distributed formation maintenance for multiple UAVs: Exploiting proximity behavior observations

Abstract

The formation maintenance of multiple unmanned aerial vehicles (UAVs) based on proximity behavior is explored in this study. Individual decision-making is conducted according to the expected UAV formation structure and the position, velocity, and attitude information of other UAVs in the azimuth area. This resolves problems wherein nodes are necessarily strongly connected and communication is strictly consistent under the traditional distributed formation control method. An adaptive distributed formation flight strategy is established for multiple UAVs by exploiting proximity behavior observations, which remedies the poor flexibility in distributed formation. This technique ensures consistent position and attitude among UAVs. In the proposed method, the azimuth area relative to the UAV itself is established to capture the state information of proximal UAVs. The dependency degree factor is introduced to state update equation based on proximity behavior. Finally, the formation position, speed, and attitude errors are used to form an adaptive dynamic adjustment strategy. Simulations are conducted to demonstrate the effectiveness and robustness of the theoretical results, thus validating the effectiveness of the proposed method.

Keywords

unmanned aerial vehicle / formation maintenance / proximity behavior / adaptive distributed control / formation flight control

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