Resilient Multi-Dimensional Consensus and Containment Control of Multi-UAV Networks in Adversarial Environments
Practical large-scale multiple unmanned aerial vehicle (multi-UAV) networks are susceptible to multiple potential points of vulnerability, such as hardware failures or adversarial attacks. Existing resilient multi-dimensional coordination control algorithms in multi-UAV networks are rather costly in...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/9/6/428 |
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| Summary: | Practical large-scale multiple unmanned aerial vehicle (multi-UAV) networks are susceptible to multiple potential points of vulnerability, such as hardware failures or adversarial attacks. Existing resilient multi-dimensional coordination control algorithms in multi-UAV networks are rather costly in the computation of a safe point and rely on an assumption of the maximum number of adversarial nodes in the multi-UAV network or neighborhood. In this paper, a dynamic trusted convex hull method is proposed to filter received states in multi-dimensional space without requiring assumptions about the maximum adversaries. Based on the proposed method, a distributed local control protocol is designed with lower computational complexity and higher tolerance of adversarial nodes. Sufficient and necessary graph-theoretic conditions are obtained to achieve resilient multi-dimensional consensus and containment control despite adversarial nodes’ behaviors. The theoretical results are validated through simulations. |
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| ISSN: | 2504-446X |