Adaptive Resilient Distributed Average Tracking of Multiagent Systems

This paper tackles the problem of achieving distributed average tracking in a multi-agent system in the presence of network attacks. Traditionally, controllers are designed using Laplacian matrix eigenvalues, but practical limitations of obtaining global information necessitate a fully distributed design. This study relies solely on agents’ local information from their neighbors, introducing adaptive parameters to develop the adaptive resilient distributed average tracking method. This fully distributed method aims to enable distributed average tracking among agents within an undirected graph, even when faced with bounded attacks. Theoretical findings are validated through simulation examples.