Fixed-Time Adaptive Synchronization of Fractional-Order Memristive Fuzzy Neural Networks with Time-Varying Leakage and Transmission Delays

Finite-time synchronization depends on the initial conditions of the system in question. However, the initial conditions of an actual system are often difficult to estimate or even unknown. Therefore, a more valuable and pressing problem is fixed-time synchronization (FTS). This paper addresses the issue of FTS for a specific class of fractional-order memristive fuzzy neural networks (FOMFNNs) that include both leakage and transmission delays. We have designed two distinct discontinuous control methodologies that account for these delays: a state feedback control scheme and a fractional-order adaptive control strategy. Leveraging differential inclusion theory and fractional-order differential inequalities, we derive several novel algebraic conditions that are independent of delay. These conditions ensure the FTS of drive–response FOMFNNs in the presence of leakage and transmission delays. Additionally, we provide an estimate for the upper bound of the settling time required to achieve FTS. Finally, to validate the feasibility and applicability of our theoretical findings, we present two numerical examples which are accompanied by simulations.

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Publication Details

Journal
Fractal and Fractional
Published
2025-04-11
DOI
https://doi.org/10.3390/fractalfract9040241
Citations
1
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
1.49

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article

Fixed-Time Adaptive Synchronization of Fractional-Order Memristive Fuzzy Neural Networks with Time-Varying Leakage and Transmission Delays

Yeguo Sun, Yihong Liu, Lei Liu
1 citations
Fractal and Fractional
Neural Networks Stability and Synchronization
1.49
article

Fixed-Time Adaptive Synchronization of Fractional-Order Memristive Fuzzy Neural Networks with Time-Varying Leakage and Transmission Delays

Yeguo Sun, Yihong Liu, Lei Liu
article en
1 citations

Abstract

Finite-time synchronization depends on the initial conditions of the system in question. However, the initial conditions of an actual system are often difficult to estimate or even unknown. Therefore, a more valuable and pressing problem is fixed-time synchronization (FTS). This paper addresses the issue of FTS for a specific class of fractional-order memristive fuzzy neural networks (FOMFNNs) that include both leakage and transmission delays. We have designed two distinct discontinuous control methodologies that account for these delays: a state feedback control scheme and a fractional-order adaptive control strategy. Leveraging differential inclusion theory and fractional-order differential inequalities, we derive several novel algebraic conditions that are independent of delay. These conditions ensure the FTS of drive–response FOMFNNs in the presence of leakage and transmission delays. Additionally, we provide an estimate for the upper bound of the settling time required to achieve FTS. Finally, to validate the feasibility and applicability of our theoretical findings, we present two numerical examples which are accompanied by simulations.

Fractal and FractionalVol. 9(4)
Huainan Normal University (CN)
Natural Science Foundation of Anhui Province
Openalex Percentile: Top 18%
Neural Networks Stability and Synchronization
1.49
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