Fixed-time and prescribed-time synchronization of quaternion-valued neural networks: A control strategy involving Lyapunov functions

被引：16
作者：
Peng, Tao [1 ,2 ]
Wu, Yanqiu [1 ]
Tu, Zhengwen [1 ]
Alofi, A. S. [4 ]
Lu, Jianquan [2 ,3 ]
机构：
[1] Chongqing Three Gorges Univ, Sch Math & Stat, Wanzhou 404100, Peoples R China
[2] Southeast Univ, Sch Math, Dept Syst Sci, Nanjing 210096, Peoples R China
[3] Linyi Univ, Sch Automation & Elect Engn, Linyi 276005, Peoples R China
[4] King Abdulaziz Univ, Fac Sci, Dept Math, Jeddah 21589, Saudi Arabia
来源：
NEURAL NETWORKS | 2023年 / 160卷
基金：
中国国家自然科学基金;
关键词：
Finite -time synchronization; Prescribed -time synchronization; Quaternion-valued neural networks; FINITE-TIME; STABILIZATION; STABILITY; SYSTEMS;
D O I：
10.1016/j.neunet.2022.12.014
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A control strategy containing Lyapunov functions is proposed in this paper. Based on this strategy, the fixed-time synchronization of a time-delay quaternion-valued neural network (QVNN) is analyzed. This strategy is extended to the prescribed-time synchronization of the QVNN. Furthermore, an improved two-step switching control strategy is also proposed based on this flexible control strategy. Compared with some existing methods, the main method of this paper is a non-decomposition one, does not contain a sign function in the controller, and has better synchronization accuracy. Two numerical examples verify the above advantages.(c) 2022 Elsevier Ltd. All rights reserved.
引用
收藏
页码：108 / 121
页数：14
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