Finite-time stabilization for fractional-order inertial neural networks with time varying delays
Articles
Chaouki Aouiti
University of Carthage
https://orcid.org/0000-0002-8252-9017
Jinde Cao
Southeast University
https://orcid.org/0000-0003-3133-7119
Hediene Jallouli
University of Carthage
https://orcid.org/0000-0002-5936-6803
Chuangxia Huang
Changsha University of Science and Technology
Published 2022-01-01
https://doi.org/10.15388/namc.2022.27.25184
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Keywords

inertial neural networks
finite-time stabilization
fractional-order system
Caputo fractional derivative and integral

How to Cite

Aouiti C., Cao J., Jallouli H. and Huang C. (2022) “Finite-time stabilization for fractional-order inertial neural networks with time varying delays”, Nonlinear Analysis: Modelling and Control, 27(1), pp. 1-18. doi: 10.15388/namc.2022.27.25184.

Abstract

This paper deals with the finite-time stabilization of fractional-order inertial neural network with varying time-delays (FOINNs). Firstly, by correctly selected variable substitution, the system is transformed into a first-order fractional differential equation. Secondly, by building Lyapunov functionalities and using analytical techniques, as well as new control algorithms (which include the delay-dependent and delay-free controller), novel and effective criteria are established to attain the finite-time stabilization of the addressed system. Finally, two examples are used to illustrate the effectiveness and feasibility of the obtained results.

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