Fixed Emergent Output Values and Their Use for Blind Matching in a Class of Decoupled Heterogeneous Multiagent Systems

This study focuses on the theoretical analysis of an emergent behavior in a class of heterogeneous multi-agent systems (HMASs) with single-input-single-output dynamics. The primary objective is to design a control law ensuring the asymptotic convergence of agents' outputs to a predefined region where the final positions of the agents represent an emergent characteristics of the considered HMAS. This emergent behavior, termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">blind matching</i>, allows completely decoupled swarms to achieve coupled consensus within a predefined region, despite lacking direct communication and exhibiting diverse initial conditions and dynamics. Applying the analysis to coordinate two swarms of double integrator agents in a two-dimensional space, the study formulates control protocols that guide agents along specific paths, establish consensus between corresponding agents, and ensure convergence to fixed positions within a defined boundary relative to chosen movement profiles. The matching problem is addressed, considering the independent nature of the swarms and their lack of direct communication.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-06-06
DOI
https://doi.org/10.1109/tac.2025.3576915
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Fixed Emergent Output Values and Their Use for Blind Matching in a Class of Decoupled Heterogeneous Multiagent Systems

Luigi D’Alfonso, Giuseppe Fedele
IEEE Transactions on Automatic Control
Neural Networks and Applications
article

Fixed Emergent Output Values and Their Use for Blind Matching in a Class of Decoupled Heterogeneous Multiagent Systems

Luigi D’Alfonso, Giuseppe Fedele
article en

Abstract

This study focuses on the theoretical analysis of an emergent behavior in a class of heterogeneous multi-agent systems (HMASs) with single-input-single-output dynamics. The primary objective is to design a control law ensuring the asymptotic convergence of agents' outputs to a predefined region where the final positions of the agents represent an emergent characteristics of the considered HMAS. This emergent behavior, termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">blind matching</i>, allows completely decoupled swarms to achieve coupled consensus within a predefined region, despite lacking direct communication and exhibiting diverse initial conditions and dynamics. Applying the analysis to coordinate two swarms of double integrator agents in a two-dimensional space, the study formulates control protocols that guide agents along specific paths, establish consensus between corresponding agents, and ensure convergence to fixed positions within a defined boundary relative to chosen movement profiles. The matching problem is addressed, considering the independent nature of the swarms and their lack of direct communication.

IEEE Transactions on Automatic ControlVol. 70(11)
University of Calabria (IT)
Openalex Percentile: Top 94%
Neural Networks and Applications
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