Resilient tracking consensus over dynamic random graphs: A linear system approach

Shang, Yilun (2023) Resilient tracking consensus over dynamic random graphs: A linear system approach. European Journal of Applied Mathematics, 34 (2). pp. 408-423. ISSN 0956-7925

Preview	Text (Final published version) resilient-tracking-consensus-over-dynamic-random-graphs-a-linear-system-approach.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (383kB) | Preview
Preview	Text (Advance online version) resilient-tracking-consensus-over-dynamic-random-graphs-a-linear-system-approach.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (488kB) | Preview
Preview	Text accepted version.pdf - Accepted Version Download (259kB) | Preview

Abstract

Cooperative coordination in multi-agent systems has been a topic of interest in networked control theory in recent years. In contrast to cooperative agents, Byzantine agents in a network are capable to manipulate their data arbitrarily and send bad messages to neighbors, causing serious network security issues. This paper is concerned with resilient tracking consensus over a time-varying random directed graph, which consists of cooperative agents, Byzantine agents and a single leader. The objective of resilient tracking consensus is the convergence of cooperative agents to the leader in the presence of those deleterious Byzantine agents. We assume that the number and identity of the Byzantine agents are not known to cooperative agents, and the communication edges in the graph are dynamically randomly evolving. Based upon linear system analysis and a martingale convergence theorem, we design a linear discrete-time protocol to ensure tracking consensus almost surely in a purely distributed manner. Some numerical examples are provided to verify our theoretical results.

Actions (login required)

View Item

Downloads