3D Self-Triggered-Organized Communication Topology Based UAV Swarm Consensus System With Distributed Extended State Observer

In this work, to address the communication topology alteration caused by unit failure or loss in the multi-UAV cooperation control system, a 3D self-triggered-organized topology (3D-STOT) based UAV swarm consensus system with distributed extended state observer (DESO) is developed. First, we propose a novel 3D self-organized topology (3D-SOT) generation method that automatically constructs adequate topology networks from swarm position information without manual intervention, with a computational complexity of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(n^{4})$</tex-math></inline-formula>. This network maintains connectivity even when a certain number of UAV failures or losses occur. Next, a 3D-STOT updating strategy is introduced to automatically update the topology based on real-time location under predefined trigger conditions. This updating strategy enables the 3D-SOT generating method to flexibly adapt to swarms of varying scales and significantly enhances the swarm system's ability to handle unexpected situations. Additionally, DESO not only supports real-time 3D-STOT updates but also assists the double-loop Sliding Mode Controller (SMC) in achieving consensus formation. Finally, the effectiveness of the proposed method is verified by simulation experiments.

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Publication Details

Journal
IEEE Transactions on Network Science and Engineering
Published
2025-05-06
DOI
https://doi.org/10.1109/tnse.2025.3567462
Citations
4
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
5.95
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article

3D Self-Triggered-Organized Communication Topology Based UAV Swarm Consensus System With Distributed Extended State Observer

Hanzhen Xiao, Dengxiu Yu, Guanyu Lai, Yang Yang et al.
4 citations
IEEE Transactions on Network Science and Engineering
Distributed Control Multi-Agent Systems
5.95
article

3D Self-Triggered-Organized Communication Topology Based UAV Swarm Consensus System With Distributed Extended State Observer

Hanzhen Xiao, Dengxiu Yu, Guanyu Lai, Yang Yang, C. L. Philip Chen
article en
4 citations

Abstract

In this work, to address the communication topology alteration caused by unit failure or loss in the multi-UAV cooperation control system, a 3D self-triggered-organized topology (3D-STOT) based UAV swarm consensus system with distributed extended state observer (DESO) is developed. First, we propose a novel 3D self-organized topology (3D-SOT) generation method that automatically constructs adequate topology networks from swarm position information without manual intervention, with a computational complexity of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(n^{4})$</tex-math></inline-formula>. This network maintains connectivity even when a certain number of UAV failures or losses occur. Next, a 3D-STOT updating strategy is introduced to automatically update the topology based on real-time location under predefined trigger conditions. This updating strategy enables the 3D-SOT generating method to flexibly adapt to swarms of varying scales and significantly enhances the swarm system's ability to handle unexpected situations. Additionally, DESO not only supports real-time 3D-STOT updates but also assists the double-loop Sliding Mode Controller (SMC) in achieving consensus formation. Finally, the effectiveness of the proposed method is verified by simulation experiments.

IEEE Transactions on Network Science and EngineeringVol. 12(5)
Guangdong University of Technology (CN), Northwestern Polytechnical University (CN), South China University of Technology (CN)
Openalex Percentile: Top 4%
Distributed Control Multi-Agent Systems
5.95
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3D Self-Triggered-Organized Communication Topology Based UAV Swarm Consensus System With Distributed Extended State Observer — Hanzhen Xiao, Dengxiu Yu, et al. · IEEE Transactions on Network Science and Engineering (2025) | TGRS Research Map | TGRS