Finite-time stabilization for fractional-order inertial neural networks with time varying delays
Chaouki Aouiti
University of Carthage
Jinde Cao
Southeast University
Hediene Jallouli
University of Carthage
Chuangxia Huang
Changsha University of Science and Technology
Published 2022-01-01


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.


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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