Master-Slave Finite-Time Synchronization of Chaotic Fractional-Order Neural Networks under Hybrid Sampled-Data Control: An LMI Approach

作     者：Kiruthika, R. Manivannan, A. 

作者机构：Vellore Inst Technol Dept Math Chennai 600127 Tamil Nadu India 

出 版 物：《NEURAL PROCESSING LETTERS》 (Neural Process Letters)

年 卷 期：2025年第57卷第1期

页      面：1-16页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Vellore Institute of Technology 

主　　题：Neural networks Finite-time synchronization Linear matrix inequality Sampled-data control 

摘      要：In this paper, a hybrid controller with a sampled data control is investigated to achieve finite-time master-slave synchronization of delayed fractional-order neural networks (DFONNs). A Lyapunov-Krasovskii functional is constructed to obtain the sufficient conditions that incorporate delay information. For the first time, the asymptotic stability of the error system is guaranteed in a finite-time using the inequality technique and a sampled-data hybrid controller. The obtained conditions are expressed via linear matrix inequality. Notably, the proposed approach outperforms existing methods, demonstrating improved results in a comparative analysis. An explicit formula is utilized to calculate the settling time, which is significantly influenced by the fractional order 0beta = 1 .The superior performance of the proposed control method is evident, showcasing its effectiveness through numerical simulations and addressing the synchronization problem in DFONNs.