Finite-time synchronization of fractional-order memristive neural networks via feedback and periodically intermittent control

Meng Hui, Chen Wei, Jiao Zhang, Herbert Ho-Ching Iu, Rui Yao, Lin Bai

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

This paper discusses the finite-time synchronization (FTS) of fractional-order memristive neural networks (FMNNs) with time-varying delays. Firstly, based on Gronwall-Bellman inequality and the fractional-order derivative of the power function, two novel propositions on finite-time fractional functional differential inequality are built. Secondly, the feedback controller and intermittent controller designed in this paper are all delay -independent controllers, which can work even when the prior state cannot be measured or the specific time delay function is unknown. Thirdly, in addition to the traditional Lyapunov function with absolute value form, a more general and flexile Lyapunov function based on p-norm form is constructed to analyze the criteria of FTS. Meanwhile, an improved estimation of settling time of fractional system is given explicitly, which is more accurate and general than the existing results. Eventually, the validity of theoretical analysis is confirmed by numerical examples. (C) 2022 Elsevier B.V. All rights reserved.

Original languageEnglish
Article number106822
Number of pages23
JournalCommunications in Nonlinear Science and Numerical Simulation
Volume116
DOIs
Publication statusPublished - Jan 2023

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