Effect of Graph Gluing on Consensus in Networked Multi-Agent Systems

TL;DR

This paper investigates how graph gluing operations in multi-agent networks affect consensus behavior and convergence rates by analyzing spectral properties and providing simulation validation.

Contribution

It introduces a theoretical framework linking interconnection strategies to spectral properties and consensus performance in networked multi-agent systems.

Findings

Gluing operations influence the Fiedler eigenvalue and convergence rate.

Different interconnection structures alter the algebraic connectivity.

Simulation results validate the theoretical analysis.

Abstract

In this paper, the effects of graph gluing operations in networks of multi-agent systems and their impact on system performance are investigated. In many practical applications, multiple multi-agent subsystems must be interconnected through communication links to accomplish complex tasks, resulting in a larger communication network. Such interconnections modify the underlying graph topology and consequently affect the consensus behavior and convergence rate of the network. In particular, this paper examines both bridge gluing and interface gluing and analyzes how the number and structure of communication links between subsystems influence the Fiedler eigenvalue of the resulting graph. Since the Fiedler eigenvalue is directly related to the convergence rate of consensus dynamics, the proposed analysis establishes a clear relationship between interconnection strategies, algebraic connectivity, and system performance. The results provide theoretical insight into how different gluing mechanisms alter the spectral properties of the graph Laplacian and, in turn, the convergence characteristics of the networked multi-agent system. Simulation studies are presented to illustrate the theoretical findings and to validate the effectiveness of the proposed framework.