Resilient average consensus on general directed graphs in presence of cyber-attacks

Abstract

This paper proposes a resilient distributed control scheme that ensures average consensus in multi-agent systems with continuous-time single-integrator kinematics in the presence of cyber-attacks. Potential cyber-attacks considered on such systems are in the form of unknown uniformly bounded false data injection (FDI) to control input channels (actuators) and also eavesdropping attacks. The purpose of such cyber-attacks is to disturb the average consensus in multi-agent systems and also to disclose the states of agents. The proposed resilient distributed average consensus protocol includes a set of virtual variables/states being exchanged via a communication network given by a general directed graph (digraph) and is designed to make the closed-loop system stable and preserve the average consensus regardless of the existence of cyber-attacks. Unlike the existing literature, the proposed distributed average consensus framework does not require any conditions on directed graphs to be strongly connected, balanced, or symmetric. A graph-theoretical approach, Lyapunov direct method, and LaSalle’s invariance principle are used to guarantee the rigorous stability of multi-agent systems augmented with the proposed distributed algorithm. Simulation results validate the theoretical contributions of this paper.