Fixed-time control of delayed neural networks with impulsive perturbations
This paper is concerned with the fixed-time stability of delayed neural networks with impulsive perturbations. By means of inequality analysis technique and Lyapunov function method, some novel fixed-time stability criteria for the addressed neural networks are derived in terms of linear matrix ine...
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Vilnius University Press
2018-12-01
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Online Access: | http://www.zurnalai.vu.lt/nonlinear-analysis/article/view/13150 |
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doaj-6f9a39d726fd4893bee3395a488583b02020-11-25T02:34:34ZengVilnius University PressNonlinear Analysis1392-51132335-89632018-12-0123610.15388/NA.2018.6.6Fixed-time control of delayed neural networks with impulsive perturbationsJingting Hu0Guixia Sui1Xiaoxiao Lu2Xiaodi Li3University of Jinan, ChinaJinan Preschool Education College, ChinaShandong Normal University; Southeast UniversityShandong Normal University, China This paper is concerned with the fixed-time stability of delayed neural networks with impulsive perturbations. By means of inequality analysis technique and Lyapunov function method, some novel fixed-time stability criteria for the addressed neural networks are derived in terms of linear matrix inequalities (LMIs). The settling time can be estimated without depending on any initial conditions but only on the designed controllers. In addition, two different controllers are designed for the impulsive delayed neural networks. Moreover, each controller involves three parts, in which each part has different role in the stabilization of the addressed neural networks. Finally, two numerical examples are provided to illustrate the effectiveness of the theoretical analysis. http://www.zurnalai.vu.lt/nonlinear-analysis/article/view/13150fixed-time stabilitydelayed neural networksimpulsive perturbationssettling timelinear matrix inequality |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jingting Hu Guixia Sui Xiaoxiao Lu Xiaodi Li |
spellingShingle |
Jingting Hu Guixia Sui Xiaoxiao Lu Xiaodi Li Fixed-time control of delayed neural networks with impulsive perturbations Nonlinear Analysis fixed-time stability delayed neural networks impulsive perturbations settling time linear matrix inequality |
author_facet |
Jingting Hu Guixia Sui Xiaoxiao Lu Xiaodi Li |
author_sort |
Jingting Hu |
title |
Fixed-time control of delayed neural networks with impulsive perturbations |
title_short |
Fixed-time control of delayed neural networks with impulsive perturbations |
title_full |
Fixed-time control of delayed neural networks with impulsive perturbations |
title_fullStr |
Fixed-time control of delayed neural networks with impulsive perturbations |
title_full_unstemmed |
Fixed-time control of delayed neural networks with impulsive perturbations |
title_sort |
fixed-time control of delayed neural networks with impulsive perturbations |
publisher |
Vilnius University Press |
series |
Nonlinear Analysis |
issn |
1392-5113 2335-8963 |
publishDate |
2018-12-01 |
description |
This paper is concerned with the fixed-time stability of delayed neural networks with impulsive perturbations. By means of inequality analysis technique and Lyapunov function method, some novel fixed-time stability criteria for the addressed neural networks are derived in terms of linear matrix inequalities (LMIs). The settling time can be estimated without depending on any initial conditions but only on the designed controllers. In addition, two different controllers are designed for the impulsive delayed neural networks. Moreover, each controller involves three parts, in which each part has different role in the stabilization of the addressed neural networks. Finally, two numerical examples are provided to illustrate the effectiveness of the theoretical analysis.
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topic |
fixed-time stability delayed neural networks impulsive perturbations settling time linear matrix inequality |
url |
http://www.zurnalai.vu.lt/nonlinear-analysis/article/view/13150 |
work_keys_str_mv |
AT jingtinghu fixedtimecontrolofdelayedneuralnetworkswithimpulsiveperturbations AT guixiasui fixedtimecontrolofdelayedneuralnetworkswithimpulsiveperturbations AT xiaoxiaolu fixedtimecontrolofdelayedneuralnetworkswithimpulsiveperturbations AT xiaodili fixedtimecontrolofdelayedneuralnetworkswithimpulsiveperturbations |
_version_ |
1724808054889775104 |