Finite-time synchronization of T-S fuzzy memristor-based neural networks subject to algebraic constraints

This article explores the finite-time synchronization (FTS) of Takagi-Sugeno fuzzy delay-coupled memristor-based neural networks (FDCMNNs) under algebraic constraints. To better accommodate practical requirements, algebraic constraints are incorporated into the existing FDCMNNs, resulting in the for...

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Bibliographic Details
Published inInformation sciences Vol. 719; p. 122480
Main Authors Wu, Xiang, Zhang, Hai, Ye, Xiaofeng, Zhang, Hongmei, Cao, Jinde
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.11.2025
Subjects
Algebraic constraints
Delay-coupled
Finite-time synchronization
Intermittent control
T-S fuzzy
T-S fuzzy
Algebraic constraints
Delay-coupled
Intermittent control
Finite-time synchronization
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Summary:This article explores the finite-time synchronization (FTS) of Takagi-Sugeno fuzzy delay-coupled memristor-based neural networks (FDCMNNs) under algebraic constraints. To better accommodate practical requirements, algebraic constraints are incorporated into the existing FDCMNNs, resulting in the formulation of singular FDCMNNs. Subsequently, within the theoretical framework of finite-time stability under periodic intermittent control, a novel adaptive periodic intermittent control scheme is proposed. By integrating the Lyapunov direct method and LMI techniques, a sufficient condition for FTS of the studied system is derived, along with an upper bound on the synchronization time. Furthermore, the strict periodic intermittent control strategy significantly reduces control costs. To validate the theoretical findings, a numerical example is conducted, confirming the accuracy of the derived result and the effectiveness of the designed controller.
ISSN:0020-0255
DOI:10.1016/j.ins.2025.122480