Dynamic Resilient Consensus of Second-Order Multiagent Networks With a Time-Varying Malicious Agent Set

We address the problem of resilient consensus in second-order multiagent networks (MANs) with a time-varying set of malicious agents. Existing research typically assumes a static set of malicious agents. However, in real-world scenarios, network attacks and recoveries may lead to dynamic changes in the roles of agents. To overcome this challenge, a novel adaptive weighted subsequence reduction (AWSR) is proposed for resilient consensus in MANs with a dynamic malicious agent set. Based on the AWSR approach, a resilient consensus algorithm is designed for second-order MANs. Graph-theoretic conditions in the context of network robustness are derived to ensure resilient consensus in the considered MAN. We also extend the algorithm and analysis to MANs with communication delays. Finally, simulation experiments are conducted to demonstrate the effectiveness of the proposed algorithms.