A Tool for Analysis and Synthesis of Heterogeneous Multi-agent Systems under Rank-deficient Coupling

TL;DR

This paper introduces a tool for analyzing and designing heterogeneous multi-agent systems with rank-deficient coupling, enabling predictable, initialization-free behavior through the concept of blended dynamics.

Contribution

It presents a coordinate transformation and the concept of blended dynamics to analyze and synthesize heterogeneous multi-agent systems with singular coupling matrices.

Findings

Blended dynamics predict system behavior under large coupling gain.

Stability of blended dynamics ensures initialization-free operation.

The method applies to various problems like state estimation and synchronization.

Abstract

The behavior of heterogeneous multi-agent systems is studied when the coupling matrices are possibly all different and/or singular, that is, its rank is less than the system dimension. Rank-deficient coupling allows exchange of limited state information, which is suitable for the study of multi-agent systems under output coupling. We present a coordinate change that transforms the heterogeneous multi-agent system into a singularly perturbed form. The slow dynamics is still a reduced-order multi-agent system consisting of a weighted average of the vector fields of all agents, and some sub-dynamics of agents. The weighted average is an emergent dynamics, which we call a blended dynamics. By analyzing or synthesizing the blended dynamics, one can predict or design the behavior of a heterogeneous multi-agent system when the coupling gain is sufficiently large. For this result, stability of the blended dynamics is required. Since stability of the individual agent is not asked, the stability of the blended dynamics is the outcome of trading off the stability among the agents. It can be seen that, under the stability of the blended dynamics, the initial conditions of the individual agents are forgotten as time goes on, and thus, the behavior of the synthesized multi-agent system is initialization-free and is suitable for plug-and-play operation. As a showcase, we apply the proposed tool to four application problems; distributed state estimation for linear systems, practical synchronization of heterogeneous Van der Pol oscillators, estimation of the number of nodes in a network, and a problem of distributed optimization.