Fixed-time Synchronization of Fractional-order Hopfield Neural Networks

被引：4

作者：

Mei, Xu ^{[1
]}

Ding, Yucai ^{[1
]}

机构：

[1] Southwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China

来源：

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2022年 / 20卷 / 11期

关键词：

Feedback controller; fixed-time synchronization; fractional order; Hopfield neural networks; SLIDING-MODE CONTROL; ROBUST STABILITY; SYSTEMS; STABILIZATION;

D O I：

10.1007/s12555-021-0529-7

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper investigates the fixed-time synchronization of fractional-order Hopfield neural networks (FHNNs). The aim of this paper is to design a state-feedback controller to make the synchronization error convergent to zero within bounded time. Based on the Lyapunov function and fractional calculus theory, we derived some criteria of synchronization for delay-free FHNNs and delayed FHNNs, respectively. At the same time, the upper bound of settling time for synchronization are given. Numerical simulations demonstrate the effectiveness of the theoretical analysis.

引用

页码：3584 / 3591

页数：8

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