Resilient Multi-Dimensional Consensus and Containment Control of Multi-UAV Networks in Adversarial Environments - Peng Zhang; Zhenghua Liu; Kai Li; Sentang Wu; Lianhe Luo (Drones)
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.