Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay

In the work we proposed the model of immunosensor, which is based on the system of lattice differential equations with delay. The conditions of local asymptotic stability for endemic state are gotten. For this purpose we have used method of Lyapunov functionals. It combines general approach to const...

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Main Authors: Vasyl Martsenyuk, Aleksandra Kłos-Witkowska, Andriy Sverstiuk
Format: Article
Language:English
Published: University of Szeged 2018-05-01
Series:Electronic Journal of Qualitative Theory of Differential Equations
Subjects:
Online Access:http://www.math.u-szeged.hu/ejqtde/periodica.html?periodica=1&paramtipus_ertek=publication&param_ertek=6354
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spelling doaj-c683ed43990d43cf810d348dbc2001a12021-07-14T07:21:31ZengUniversity of SzegedElectronic Journal of Qualitative Theory of Differential Equations1417-38751417-38752018-05-0120182713110.14232/ejqtde.2018.1.276354Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delayVasyl Martsenyuk0Aleksandra Kłos-Witkowska1Andriy Sverstiuk2University of Bielsko-Biala, Department of Computer Science, Bielsko-Biala, PolandDepartment of Computer Science and Automatics, University of Bielsko-Biala, Bielsko-Biala, PolandDepartment of Medical Informatics, Ternopil State Medical University, Ternopil, UkraineIn the work we proposed the model of immunosensor, which is based on the system of lattice differential equations with delay. The conditions of local asymptotic stability for endemic state are gotten. For this purpose we have used method of Lyapunov functionals. It combines general approach to construction of Lyapunov functionals of the predator–prey models with lattice differential equations. Numerical examples have showed the influence on stability of model parameters. From our numerical simulations, we have found evidence that chaos can occur through variation in the time delay. Namely, as the time delay was increased, the stable endemic solution changed at a critical value of $\tau$ to a stable limit cycle. Further, when increasing the time delay, the behavior changed from convergence to simple limit cycle to convergence to complicated limit cycles with an increasing number of local maxima and minima per cycle until at sufficiently high time delay the behavior became chaotic.http://www.math.u-szeged.hu/ejqtde/periodica.html?periodica=1&paramtipus_ertek=publication&param_ertek=6354biosensorimmunosensorlattice differential equationsdifferential equations with delayasymptotic stabilitylyapunov functionalbifurcationchaos
collection DOAJ
language English
format Article
sources DOAJ
author Vasyl Martsenyuk
Aleksandra Kłos-Witkowska
Andriy Sverstiuk
spellingShingle Vasyl Martsenyuk
Aleksandra Kłos-Witkowska
Andriy Sverstiuk
Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
Electronic Journal of Qualitative Theory of Differential Equations
biosensor
immunosensor
lattice differential equations
differential equations with delay
asymptotic stability
lyapunov functional
bifurcation
chaos
author_facet Vasyl Martsenyuk
Aleksandra Kłos-Witkowska
Andriy Sverstiuk
author_sort Vasyl Martsenyuk
title Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
title_short Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
title_full Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
title_fullStr Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
title_full_unstemmed Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
title_sort stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
publisher University of Szeged
series Electronic Journal of Qualitative Theory of Differential Equations
issn 1417-3875
1417-3875
publishDate 2018-05-01
description In the work we proposed the model of immunosensor, which is based on the system of lattice differential equations with delay. The conditions of local asymptotic stability for endemic state are gotten. For this purpose we have used method of Lyapunov functionals. It combines general approach to construction of Lyapunov functionals of the predator–prey models with lattice differential equations. Numerical examples have showed the influence on stability of model parameters. From our numerical simulations, we have found evidence that chaos can occur through variation in the time delay. Namely, as the time delay was increased, the stable endemic solution changed at a critical value of $\tau$ to a stable limit cycle. Further, when increasing the time delay, the behavior changed from convergence to simple limit cycle to convergence to complicated limit cycles with an increasing number of local maxima and minima per cycle until at sufficiently high time delay the behavior became chaotic.
topic biosensor
immunosensor
lattice differential equations
differential equations with delay
asymptotic stability
lyapunov functional
bifurcation
chaos
url http://www.math.u-szeged.hu/ejqtde/periodica.html?periodica=1&paramtipus_ertek=publication&param_ertek=6354
work_keys_str_mv AT vasylmartsenyuk stabilitybifurcationandtransitiontochaosinamodelofimmunosensorbasedonlatticedifferentialequationswithdelay
AT aleksandrakłoswitkowska stabilitybifurcationandtransitiontochaosinamodelofimmunosensorbasedonlatticedifferentialequationswithdelay
AT andriysverstiuk stabilitybifurcationandtransitiontochaosinamodelofimmunosensorbasedonlatticedifferentialequationswithdelay
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