Distributed Non-Uniform Scaling Control of Multi-Agent Formation with Dynamic Agent Joining

2026-05-27

AI Summary

This work addresses the limitation of existing non-uniform scaling formation control methods, which typically assume a fixed number of agents and thus struggle to accommodate dynamic membership changes in real-world scenarios. The paper proposes a novel distributed control framework that, for the first time, enables seamless integration of new agents during non-uniform scaling formations in arbitrary dimensions while rigorously preserving the spectral properties of the communication graph’s Laplacian matrix. By integrating graph theory, distributed control theory, and Laplacian spectral analysis, the approach guarantees both system stability and task continuity. Simulation results demonstrate its effectiveness in maintaining formation geometry and seamlessly incorporating new members across multidimensional spaces, significantly enhancing the flexibility and scalability of multi-agent systems.

Abstract

Non-uniform scaling control of formation enables multi-agent systems to adjust their shape by scaling with different ratios along different coordinate axes, offering enhanced flexibility in complex environments. However, like most existing formation maneuver strategies, it typically assumes a fixed set of agents, limiting its applicability in scenarios requiring dynamic team expansion. This paper introduces a distributed control framework that enables a formation to incorporate new agents during non-uniform scaling maneuvers in arbitrary dimensions while preserving the spectral properties of the graph Laplacian. Simulation examples validate the effectiveness of the theoretical results.

Problem

• non-uniform scaling
• multi-agent formation
• dynamic agent joining
• distributed control
• graph Laplacian

Innovation

• distributed control
• non-uniform scaling
• dynamic agent joining
• formation control
• graph Laplacian