Core Concepts
The authors propose a scale-free framework for achieving δ-level coherent state synchronization of multi-agent systems in the presence of bounded disturbances/noises, without requiring any prior knowledge about the network or the size of the disturbances.
Abstract
The paper studies the problem of scalable δ-level coherent state synchronization for multi-agent systems (MAS) subject to bounded disturbances/noises. The key contributions are:
The proposed protocols are designed solely based on the knowledge of the agent models, without any information about the communication network such as bounds on the spectrum of the associated Laplacian matrix or the number of agents. The protocols are scale-free and work for any connected communication network.
The authors achieve scalable δ-level coherent state synchronization, where for any given δ, the level of coherency of the network can be restricted to δ. The only assumption is that the disturbances are bounded, but the protocol is independent of the bound and does not require any other knowledge about the disturbances.
The paper first introduces the problem formulation and the necessary preliminaries on graph theory. It then presents the protocol design in three steps: 1) finding the matrix P, 2) choosing the parameter d, and 3) obtaining the adaptive protocol. The authors prove that the proposed protocol solves the δ-level coherent state synchronization problem in the presence of bounded disturbances/noises for any connected communication network.