Effect of Graph Gluing on Consensus in Networked Multi-Agent Systems
For control engineers designing interconnected multi-agent systems, this work provides theoretical insight into how communication link structure impacts consensus performance, though the results are analytical rather than empirical.
This paper analyzes how bridge and interface gluing operations affect the Fiedler eigenvalue (algebraic connectivity) of graphs in networked multi-agent systems, establishing a relationship between interconnection strategies and consensus convergence rate. Simulation studies validate the theoretical findings.
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.