Stability analysis of stochastic and random systems in the Lyapunov sense

Lyapunov approach plays a vital role in addressing the issue of stability in deterministic and random (stochastic) systems. This paper is involved in the study of stability of linear and nonlinear systems perturbed by a standard Brownian motion, random coefficients or coefficient functions acting as...

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Autor principal:	I.M. Elbaz
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Random and stochastic systems Mean-square stability Lyapunov functions Stability analysis Brownian motion Applied mathematics. Quantitative methods T57-57.97
Acceso en línea:	https://doaj.org/article/2e8df8daf77e48c0b35dde086b75c13a
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spelling	oai:doaj.org-article:2e8df8daf77e48c0b35dde086b75c13a2021-12-04T04:36:23ZStability analysis of stochastic and random systems in the Lyapunov sense2666-720710.1016/j.rico.2021.100060https://doaj.org/article/2e8df8daf77e48c0b35dde086b75c13a2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666720721000357https://doaj.org/toc/2666-7207Lyapunov approach plays a vital role in addressing the issue of stability in deterministic and random (stochastic) systems. This paper is involved in the study of stability of linear and nonlinear systems perturbed by a standard Brownian motion, random coefficients or coefficient functions acting as stochastic processes. We mainly focus on the stability in mean-square and stochastic stability of these systems. Some suitable Lyapunov functions imply the necessary conditions of mean-square stability and stability in probability. Stability of systems with random variable coefficients are firstly discussed in this paper. The theoretical findings are supported by some examples with stability regions and some numerical simulations.I.M. ElbazElsevierarticleRandom and stochastic systemsMean-square stabilityLyapunov functionsStability analysisBrownian motionApplied mathematics. Quantitative methodsT57-57.97ENResults in Control and Optimization, Vol 5, Iss , Pp 100060- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Random and stochastic systems Mean-square stability Lyapunov functions Stability analysis Brownian motion Applied mathematics. Quantitative methods T57-57.97
spellingShingle	Random and stochastic systems Mean-square stability Lyapunov functions Stability analysis Brownian motion Applied mathematics. Quantitative methods T57-57.97 I.M. Elbaz Stability analysis of stochastic and random systems in the Lyapunov sense
description	Lyapunov approach plays a vital role in addressing the issue of stability in deterministic and random (stochastic) systems. This paper is involved in the study of stability of linear and nonlinear systems perturbed by a standard Brownian motion, random coefficients or coefficient functions acting as stochastic processes. We mainly focus on the stability in mean-square and stochastic stability of these systems. Some suitable Lyapunov functions imply the necessary conditions of mean-square stability and stability in probability. Stability of systems with random variable coefficients are firstly discussed in this paper. The theoretical findings are supported by some examples with stability regions and some numerical simulations.
format	article
author	I.M. Elbaz
author_facet	I.M. Elbaz
author_sort	I.M. Elbaz
title	Stability analysis of stochastic and random systems in the Lyapunov sense
title_short	Stability analysis of stochastic and random systems in the Lyapunov sense
title_full	Stability analysis of stochastic and random systems in the Lyapunov sense
title_fullStr	Stability analysis of stochastic and random systems in the Lyapunov sense
title_full_unstemmed	Stability analysis of stochastic and random systems in the Lyapunov sense
title_sort	stability analysis of stochastic and random systems in the lyapunov sense
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/2e8df8daf77e48c0b35dde086b75c13a
work_keys_str_mv	AT imelbaz stabilityanalysisofstochasticandrandomsystemsinthelyapunovsense
_version_	1718372902676463616

Stability analysis of stochastic and random systems in the Lyapunov sense

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