Control design and analysis of an epidemic seiv model upon adaptive network

Li, Z; Hong, J; Kim, J; Yu, C

Control design and analysis of an epidemic seiv model upon adaptive network

Li, Z Hong, J Kim, J

Yu, C

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Publication Type:: Conference Proceeding
Citation:: 2019 18th European Control Conference, ECC 2019, 2019, pp. 2492 - 2497
Issue Date:: 2019-06-01

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Field	Value	Language
dc.contributor.author	Li, Z	en_US
dc.contributor.author	Hong, J	en_US
dc.contributor.author	Kim, J https://orcid.org/0000-0003-4505-1103	en_US
dc.contributor.author	Yu, C	en_US
dc.date.issued	2019-06-01	en_US
dc.identifier.citation	2019 18th European Control Conference, ECC 2019, 2019, pp. 2492 - 2497	en_US
dc.identifier.isbn	9783907144008	en_US
dc.identifier.uri	http://hdl.handle.net/10453/137113
dc.description.abstract	© 2019 EUCA. This paper focuses on the control design and stability analysis of a Susceptible-Exposed-Infected-Vigilant (SEIV) epidemic model via adaptive complex networks. The network is designed empirically as a state-dependent network, where the network structure keeps changing to inhibit the epidemic propagation. The recovery rate and the disease prevention rate are chosen as the control scheme in the epidemic system, both of which are closely associated with medical resources allocation. People may cut the connection with an infected neighbor and reduce the frequency to go out when an epidemic occurs. In order to formulate this behavior, an adaptive network structure is presented which is designed to be consistent with real human contact behaviors under epidemic prevalence. A candidate Lyapunov function is employed to analyze the system stability and guarantee the extinction of the epidemic. Simulation results are shown to illustrate the high efficiency and validity of the parameter control and the adaptive network design.	en_US
dc.relation.ispartof	2019 18th European Control Conference, ECC 2019	en_US
dc.relation.isbasedon	10.23919/ECC.2019.8796023	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Control design and analysis of an epidemic seiv model upon adaptive network	en_US
dc.type	Conference Proceeding
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2019 EUCA. This paper focuses on the control design and stability analysis of a Susceptible-Exposed-Infected-Vigilant (SEIV) epidemic model via adaptive complex networks. The network is designed empirically as a state-dependent network, where the network structure keeps changing to inhibit the epidemic propagation. The recovery rate and the disease prevention rate are chosen as the control scheme in the epidemic system, both of which are closely associated with medical resources allocation. People may cut the connection with an infected neighbor and reduce the frequency to go out when an epidemic occurs. In order to formulate this behavior, an adaptive network structure is presented which is designed to be consistent with real human contact behaviors under epidemic prevalence. A candidate Lyapunov function is employed to analyze the system stability and guarantee the extinction of the epidemic. Simulation results are shown to illustrate the high efficiency and validity of the parameter control and the adaptive network design.

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http://hdl.handle.net/10453/137113