TY - GEN
T1 - Fully Distributed Dynamic Event-Triggering Formation Control of UAV Swarms under DoS Attacks
AU - Cao, Hui
AU - Han, Liang
AU - Li, Dongyu
AU - Hu, Qinglei
AU - Hao, Pengkun
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - For large-scale unmanned aerial vehicle (UAV) swarms, the security of communication networks is critical. When subjected to cyberattacks, the performance of swarm systems will be significantly affected. This paper focuses on the fully distributed time-varying formation (TVF) control problem of UAV swarms under Denial-of-Service (DoS) attacks. First, the theoretical framework of the fully distributed dynamic event-triggering TVF control protocol is introduced. Then, sufficient conditions and critical proofs are provided to demonstrate that the desired formation configuration can be achieved under the influence of DoS attacks, and Zeno behavior is eliminated. Finally, the framework of a mixed-reality swarm flight platform is presented, which includes virtual nodes and physical nodes and integrates the advantages of both simulation and physical experiments, enabling large-scale swarm experiments with less cost and higher efficiency. The formation experiment using this platform validates the efficacy of the proposed control protocol.
AB - For large-scale unmanned aerial vehicle (UAV) swarms, the security of communication networks is critical. When subjected to cyberattacks, the performance of swarm systems will be significantly affected. This paper focuses on the fully distributed time-varying formation (TVF) control problem of UAV swarms under Denial-of-Service (DoS) attacks. First, the theoretical framework of the fully distributed dynamic event-triggering TVF control protocol is introduced. Then, sufficient conditions and critical proofs are provided to demonstrate that the desired formation configuration can be achieved under the influence of DoS attacks, and Zeno behavior is eliminated. Finally, the framework of a mixed-reality swarm flight platform is presented, which includes virtual nodes and physical nodes and integrates the advantages of both simulation and physical experiments, enabling large-scale swarm experiments with less cost and higher efficiency. The formation experiment using this platform validates the efficacy of the proposed control protocol.
UR - https://www.scopus.com/pages/publications/85184795578
U2 - 10.1109/CDC49753.2023.10384259
DO - 10.1109/CDC49753.2023.10384259
M3 - 会议稿件
AN - SCOPUS:85184795578
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 3166
EP - 3173
BT - 2023 62nd IEEE Conference on Decision and Control, CDC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 62nd IEEE Conference on Decision and Control, CDC 2023
Y2 - 13 December 2023 through 15 December 2023
ER -