Global Mittag-Leffler Projective Synchronization of Distinct Fractional-order Delayed Neural Networks with Inconsistent Orders and Interaction Terms via integral Sliding Mode Control

Abstract This work focuses on the global Mittag–Leffler projective synchronization (GMLPS) of distinct fractional-order delayed neural networks (FODNNs) with inconsistent orders and interaction terms. Initially, a delayed fractional-order (FO) integral sliding surface is made by embedding the FO gradient fed into the controller, facilitating the formulation of a synchronous error system. Subsequently, a delayed sliding mode controller (SMC) is formulated using the sliding mode control theory to guarantee the occurrence of the sliding motion. Furthermore, error systems are shown to converge to the predefined sliding surface, enabling sliding motion through the fractional Lyapunov direct approach and the Razumikhin method. Novel criteria are established to achieve the GMLPS for distinct FODNNs with inconsistent orders and interaction terms. Finally, numerical experiments are exploited to highlight the performance of the obtained outcomes.

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Publication Details

Journal
Neural Processing Letters
Published
2025-08-04
DOI
https://doi.org/10.1007/s11063-025-11793-3
Citations
8
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
11.90
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article

Global Mittag-Leffler Projective Synchronization of Distinct Fractional-order Delayed Neural Networks with Inconsistent Orders and Interaction Terms via integral Sliding Mode Control

S. Dharani, G Pavithra
8 citations
Neural Processing Letters
Neural Networks Stability and Synchronization
11.90
article

Global Mittag-Leffler Projective Synchronization of Distinct Fractional-order Delayed Neural Networks with Inconsistent Orders and Interaction Terms via integral Sliding Mode Control

S. Dharani, G Pavithra
article en
8 citations

Abstract

Abstract This work focuses on the global Mittag–Leffler projective synchronization (GMLPS) of distinct fractional-order delayed neural networks (FODNNs) with inconsistent orders and interaction terms. Initially, a delayed fractional-order (FO) integral sliding surface is made by embedding the FO gradient fed into the controller, facilitating the formulation of a synchronous error system. Subsequently, a delayed sliding mode controller (SMC) is formulated using the sliding mode control theory to guarantee the occurrence of the sliding motion. Furthermore, error systems are shown to converge to the predefined sliding surface, enabling sliding motion through the fractional Lyapunov direct approach and the Razumikhin method. Novel criteria are established to achieve the GMLPS for distinct FODNNs with inconsistent orders and interaction terms. Finally, numerical experiments are exploited to highlight the performance of the obtained outcomes.

Neural Processing LettersVol. 57(4)
Vellore Institute of Technology University (IN)
Openalex Percentile: Top 2%
Neural Networks Stability and Synchronization
11.90
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