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Analysis and Distributed Control of Periodic Epidemic Processes
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0002-2136-3957
Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA.ORCID iD: 0000-0002-4095-7320
KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0003-1835-2963
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9940-5929
2021 (English)In: IEEE Transactions on Control of Network Systems, E-ISSN 2325-5870, Vol. 8, no 1, p. 123-134Article in journal (Refereed) Published
Abstract [en]

This article studies epidemic processes over discrete-time periodic time-varying networks. We focus on the susceptible-infected-susceptible (SIS) model that accounts for a (possibly) mutating virus. We say that an agent is in the disease-free state if it is not infected by the virus. Our objective is to devise a control strategy which ensures that all agents in a network exponentially (respectively asymptotically) converge to the disease-free equilibrium (DFE). Toward this end, we first provide 1) sufficient conditions for exponential (respectively, asymptotic) convergence to the DFE and 2) a necessary and sufficient condition for asymptotic convergence to the DFE. The sufficient condition for global exponential stability (GES) [respectively global asymptotic stability (GAS)] of the DFE is in terms of the joint spectral radius of a set of suitably defined matrices, whereas the necessary and sufficient condition for GAS of the DFE involves the spectral radius of an appropriately defined product of matrices. Subsequently, we leverage the stability results in order to design a distributed control strategy for eradicating the epidemic.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. Vol. 8, no 1, p. 123-134
Keywords [en]
Discrete-time networks, distributed control strategy, epidemic processes, global asymptotic stability (GAS), global exponential stability (GES), susceptible-infected-susceptible (SIS) models, time-varying systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-293581DOI: 10.1109/TCNS.2020.3017717ISI: 000626322000011Scopus ID: 2-s2.0-85091352412OAI: oai:DiVA.org:kth-293581DiVA, id: diva2:1555998
Note

QC 20210519

Available from: 2021-05-19 Created: 2021-05-19 Last updated: 2025-03-18Bibliographically approved

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Gracy, SebinPare, Philip E.Sandberg, HenrikJohansson, Karl H.

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