Abstract

Multiscale consensus has been studied recently as a new concept in the field of multi-agent systems, which is able to accommodate many complicated coordination control tasks where values are measured in different scales due to, e.g., the constraints of physical environment. In this paper, we investigate the problem of resilient multiscale coordination control against a set of adversarial or non-cooperative nodes in directed networks. We design a multiscale filtering algorithm based upon local information which can withstand both faulty and Byzantine nodes. Building on the concept of network robustness, we establish necessary and sufficient conditions guaranteeing multiscale consensus with general time varying scales in the presence of globally bounded as well as locally bounded threats. In particular, for a network containing at most $\mathsf{R}$ faulty nodes, multiscale consensus is achieved if and only if the network is $(\mathsf{R}+\mathsf{1},\mathsf{R}+\mathsf{1})$-robust. The counterpart when having at most $\mathsf{R}$ Byzantine nodes instead is that the induced subnetwork of cooperative nodes is $\mathsf{R}+\mathsf{1}$-robust. Conditions guaranteeing resilient consensus for time-dependent networks are developed. Moreover, multiscale formation generation problems are introduced and solved as the generalizations. Finally, some numerical examples including applications in modular microgrids and power systems are worked out to demonstrate the availability of our theoretical results. View Full-Text