Scalable δ-Level Coherent State Synchronization of Multi-Agent Systems in the Presence of Bounded Disturbances

Abstract

In this paper, we study scalable $\hat{I}´-$level coherent state synchronization for multi-agent systems (MAS) where the agents are subject to bounded disturbances/noises. We propose a scale-free framework designed solely based on the knowledge of agent models and agnostic to the communication graph and the size of the network. We define the level of coherency for each agent as the norm of the weighted sum of the disagreement dynamics with its neighbors. The objective is to restrict the network's coherency level to $\hat{I}´$ without a-priori information about the disturbance.

25 pages, 15 figures, This is a preprint of the paper "Scalable δ-Level Coherent State Synchronization of Multi-Agent Systems with Adaptive Protocols and Bounded Disturbances" submitted to the International Journal of Adaptive Control & Signal Processing