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Auteurs principaux: Fang, Qin, Diagne, Mamadou, Zhu, Yang
Format: Preprint
Publié: 2025
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Accès en ligne:https://arxiv.org/abs/2512.24735
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author Fang, Qin
Diagne, Mamadou
Zhu, Yang
author_facet Fang, Qin
Diagne, Mamadou
Zhu, Yang
contents This paper investigates the output synchronization problem for discrete-time heterogeneous multi-agent systems (MASs) subject to distinct communication delays. The presence of such delays prevents the instantaneous delivery of information from neighboring nodes, thereby severely degrading the performance of standard distributed control schemes. To overcome this, we propose a prediction-based framework for exact delay compensation. Specifically, we introduce predictors combined with a mechanism of distributed predictors, which enables the recursive reconstruction of future state information across the communication network. Building upon these predictors, we construct prediction-based distributed observers and formulate both prediction-based distributed state-feedback and dynamic output-feedback controllers. Theoretical analysis confirms that the proposed strategy eliminates the impact of delays after a finite number of steps, ensuring output synchronization. The effectiveness of the methods is validated through a numerical example and a Koopman operator-based linear Susceptible-Infected-Recovered (SIR) epidemic model. Notably, for a population of 4 million, the proposed delay compensation strategy achieves a reduction of over 200,000 infected individuals at the peak, underscoring its potential significance in epidemic mitigation.
format Preprint
id arxiv_https___arxiv_org_abs_2512_24735
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Exact compensation of communication delays for discrete-time heterogeneous multi-agent linear systems with applications to SIR epidemic model
Fang, Qin
Diagne, Mamadou
Zhu, Yang
Systems and Control
This paper investigates the output synchronization problem for discrete-time heterogeneous multi-agent systems (MASs) subject to distinct communication delays. The presence of such delays prevents the instantaneous delivery of information from neighboring nodes, thereby severely degrading the performance of standard distributed control schemes. To overcome this, we propose a prediction-based framework for exact delay compensation. Specifically, we introduce predictors combined with a mechanism of distributed predictors, which enables the recursive reconstruction of future state information across the communication network. Building upon these predictors, we construct prediction-based distributed observers and formulate both prediction-based distributed state-feedback and dynamic output-feedback controllers. Theoretical analysis confirms that the proposed strategy eliminates the impact of delays after a finite number of steps, ensuring output synchronization. The effectiveness of the methods is validated through a numerical example and a Koopman operator-based linear Susceptible-Infected-Recovered (SIR) epidemic model. Notably, for a population of 4 million, the proposed delay compensation strategy achieves a reduction of over 200,000 infected individuals at the peak, underscoring its potential significance in epidemic mitigation.
title Exact compensation of communication delays for discrete-time heterogeneous multi-agent linear systems with applications to SIR epidemic model
topic Systems and Control
url https://arxiv.org/abs/2512.24735