Titre :

Finite/nearly Fixed-Time stability of Nonlinear Impulsive Systems with Destabilizing Impulses and its Application to Neural Networks

Auteur(s) :

Kumar, Rakesh [Auteur]
Karlsruhe Institute of Technology = Karlsruher Institut für Technologie [KIT]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]

Titre de la revue :

Communications in Nonlinear Science and Numerical Simulation

Éditeur :

Elsevier

Date de publication :

2023

ISSN :

1007-5704

Mot(s)-clé(s) en anglais :

Impulsive differential equation Stability analysis Average dwell time Neural networks Synchronization

Discipline(s) HAL :

Informatique [cs]/Automatique

Résumé en anglais : [en]

This paper investigated the finite-time stability (FTS) and nearly fixed-time stability (nFxTS) of nonlinear impulsive systems with destabilizing impulses. The concept of nFxTS is different from FxTS, as the former may be ...
Lire la suite >This paper investigated the finite-time stability (FTS) and nearly fixed-time stability (nFxTS) of nonlinear impulsive systems with destabilizing impulses. The concept of nFxTS is different from FxTS, as the former may be just asymptotically stable but the latter must be FTS. A Lyapunov inequality with linear terms has been used to derive sufficient conditions based on the dwell time (DT) and average dwell time (ADT) properties of impulsive sequences to ensure FTS/FxTS of the system. Theorems are constructed based on the initial state of the system, which belongs to either-neighbourhood(nbh) or outside-nbh of the origin. When the system starts within −nbh of the origin then FTS can be achieved by the system following conditions on DT and ADT of impulsive sequences. The same is true for nFxTS of the system when it starts outside-nbh of the origin. We investigated the condition on DT for which nFxTS is not possible, but FTS is possible only if > 0 is bounded. The main results of this paper are applied to the synchronization problem of impulsive neural networks with destablizing impulses. Finally, a numerical example of an impulsive neural network is given to illustrate the validity of the proposed theoretical results.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL