Resilient Distributed Consensus Control of Multi-QUAVs Under Limited Communication Bandwidth and DoS Attacks

To address resilient distributed consensus of multi-quadrotor unmanned aerial vehicles (QUAVs) in complex low-altitude communication environments, this paper proposes a resilient distributed consensus control strategy for multi-QUAVs subject to limited communication bandwidth and denial-of-service (DoS) attacks. Unlike existing approaches that rely on high communication frequencies or lack explicit mechanisms to handle network attacks, the proposed two-layer control architecture enables secure consensus of multi-QUAVs under constrained communication resources. An adaptive real-time compensation mechanism based on a radial basis function neural network (RBFNN) is incorporated to substantially enhance control accuracy and robustness while suppressing the effects of uncertain nonlinear dynamics. Lyapunov--based stability analysis is employed to rigorously establish asymptotic convergence of the closed--loop system under composite constraints, while systematically addressing the interplay among strong nonlinear dynamics, quantizer constraints, and security issues induced by DoS attacks. Numerical simulations validate the effectiveness of the proposed control strategy and demonstrate superior performance in terms of control accuracy, convergence speed, and robustness against the dual constraints of limited communication bandwidth and DoS attacks.