Observer‐Based Adaptive Robust Control of Dual‐Layer Multiagent Epidemic Model: Physical and Information Layers

ABSTRACT This paper proposes an innovative dual‐layer multi‐agent‐based SIS epidemic model, incorporating a physical contact layer to model disease spread through travel or migration between cities, and an information layer to enable the sharing of infection data among healthcare providers across cities even without direct physical connections. An observer is designed to estimate the infected fraction in each city, utilising estimates from neighbouring cities connected in the physical layer in a distributed manner; these estimates are then leveraged in the information layer to synchronise each city's infection trajectory with a virtual leader. Additionally, the control input, typically formulated in multi‐agent systems (MAS), is adopted as the sliding surface, with its stability demonstrated via Lyapunov analysis within the dual‐layer SIS framework. An adaptive sliding mode control (ASMC) strategy is developed to address parameter uncertainties to reach this sliding surface, effectively integrating the physical and information layers’ dynamics to drive cities toward disease eradication. Finally, a numerical example is provided to validate the accuracy of the theoretical results.

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Publication Details

Journal
IET Control Theory and Applications
Published
2025-01-01
DOI
https://doi.org/10.1049/cth2.70052
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
Field-Weighted Citation Impact
0.00

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Controls
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article

Observer‐Based Adaptive Robust Control of Dual‐Layer Multiagent Epidemic Model: Physical and Information Layers

Xinzhi Liu, Zohreh Abbasi
IET Control Theory and Applications
Mathematical and Theoretical Epidemiology and Ecology Models
article

Observer‐Based Adaptive Robust Control of Dual‐Layer Multiagent Epidemic Model: Physical and Information Layers

Xinzhi Liu, Zohreh Abbasi
article en

Abstract

ABSTRACT This paper proposes an innovative dual‐layer multi‐agent‐based SIS epidemic model, incorporating a physical contact layer to model disease spread through travel or migration between cities, and an information layer to enable the sharing of infection data among healthcare providers across cities even without direct physical connections. An observer is designed to estimate the infected fraction in each city, utilising estimates from neighbouring cities connected in the physical layer in a distributed manner; these estimates are then leveraged in the information layer to synchronise each city's infection trajectory with a virtual leader. Additionally, the control input, typically formulated in multi‐agent systems (MAS), is adopted as the sliding surface, with its stability demonstrated via Lyapunov analysis within the dual‐layer SIS framework. An adaptive sliding mode control (ASMC) strategy is developed to address parameter uncertainties to reach this sliding surface, effectively integrating the physical and information layers’ dynamics to drive cities toward disease eradication. Finally, a numerical example is provided to validate the accuracy of the theoretical results.

IET Control Theory and ApplicationsVol. 19(1)
University of Waterloo (CA)
Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 78%
Mathematical and Theoretical Epidemiology and Ecology Models
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