Relative controllability of a stochastic system using fractional delayed sine and cosine matrices

In this paper, we study the relative controllability of a fractional stochastic system with pure delay in finite  dimensional stochastic spaces. A set of sufficient conditions is obtained for relative exact controllability using fixed point theory, fractional calculus (including fractional delayed...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: JinRong Wang, T. Sathiyaraj, Donal O’Regan
Formato: article
Lenguaje:EN
Publicado: Vilnius University Press 2021
Materias:
Acceso en línea:https://doaj.org/article/d5f1784d5d3741df9cfef421367c665b
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:d5f1784d5d3741df9cfef421367c665b
record_format dspace
spelling oai:doaj.org-article:d5f1784d5d3741df9cfef421367c665b2021-12-02T19:26:51ZRelative controllability of a stochastic system using fractional delayed sine and cosine matrices10.15388/namc.2021.26.242651392-51132335-8963https://doaj.org/article/d5f1784d5d3741df9cfef421367c665b2021-11-01T00:00:00Zhttps://www.journals.vu.lt/nonlinear-analysis/article/view/24265https://doaj.org/toc/1392-5113https://doaj.org/toc/2335-8963 In this paper, we study the relative controllability of a fractional stochastic system with pure delay in finite  dimensional stochastic spaces. A set of sufficient conditions is obtained for relative exact controllability using fixed point theory, fractional calculus (including fractional delayed linear operators and Grammian matrices) and local assumptions on nonlinear terms. Finally, an example is given to illustrate our theory. JinRong WangT. SathiyarajDonal O’ReganVilnius University Pressarticlerelative controllabilityfractional delay stochastic systemsfractional delayed sine and cosine matricesAnalysisQA299.6-433ENNonlinear Analysis, Vol 26, Iss 6 (2021)
institution DOAJ
collection DOAJ
language EN
topic relative controllability
fractional delay stochastic systems
fractional delayed sine and cosine matrices
Analysis
QA299.6-433
spellingShingle relative controllability
fractional delay stochastic systems
fractional delayed sine and cosine matrices
Analysis
QA299.6-433
JinRong Wang
T. Sathiyaraj
Donal O’Regan
Relative controllability of a stochastic system using fractional delayed sine and cosine matrices
description In this paper, we study the relative controllability of a fractional stochastic system with pure delay in finite  dimensional stochastic spaces. A set of sufficient conditions is obtained for relative exact controllability using fixed point theory, fractional calculus (including fractional delayed linear operators and Grammian matrices) and local assumptions on nonlinear terms. Finally, an example is given to illustrate our theory.
format article
author JinRong Wang
T. Sathiyaraj
Donal O’Regan
author_facet JinRong Wang
T. Sathiyaraj
Donal O’Regan
author_sort JinRong Wang
title Relative controllability of a stochastic system using fractional delayed sine and cosine matrices
title_short Relative controllability of a stochastic system using fractional delayed sine and cosine matrices
title_full Relative controllability of a stochastic system using fractional delayed sine and cosine matrices
title_fullStr Relative controllability of a stochastic system using fractional delayed sine and cosine matrices
title_full_unstemmed Relative controllability of a stochastic system using fractional delayed sine and cosine matrices
title_sort relative controllability of a stochastic system using fractional delayed sine and cosine matrices
publisher Vilnius University Press
publishDate 2021
url https://doaj.org/article/d5f1784d5d3741df9cfef421367c665b
work_keys_str_mv AT jinrongwang relativecontrollabilityofastochasticsystemusingfractionaldelayedsineandcosinematrices
AT tsathiyaraj relativecontrollabilityofastochasticsystemusingfractionaldelayedsineandcosinematrices
AT donaloregan relativecontrollabilityofastochasticsystemusingfractionaldelayedsineandcosinematrices
_version_ 1718376527817605120