Synchronization and settling-time estimation of fuzzy memristive neural networks with time-varying delays: Fixed-time and preassigned-time control

被引：5
|
作者：
Wang, Leimin [1 ,2 ,3 ]
Li, Haoyu [1 ,2 ,3 ]
Hu, Cheng [4 ]
Hu, Junhao [5 ]
Wang, Qingyi [1 ,2 ,3 ]
机构：
[1] China Univ Geosci, Sch Automat, Wuhan 430074, Peoples R China
[2] Hubei Key Lab Adv Control & Intelligent Automat Co, Wuhan 430074, Peoples R China
[3] Minist Educ, Engn Res Ctr Intelligent Technol Geoexplorat, Wuhan 430074, Peoples R China
[4] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China
[5] South Cent Univ Nationalities, Coll Math & Stat, Wuhan 430074, Peoples R China
来源：
FUZZY SETS AND SYSTEMS | 2023年 / 470卷
基金：
中国国家自然科学基金;
关键词：
Synchronization; Settling-time; Fuzzy memristive neural networks; Fixed-time control; Preassigned-time control; FINITE-TIME;
D O I：
10.1016/j.fss.2023.108654
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper addresses the synchronization of fuzzy memristive neural networks (FMNNs) with time-varying delays, focusing on both fixed-time synchronization (FXTS) and preassigned-time synchronization (PTS) problems. Particularly, a delayed feedback controller is designed to achieve FXTS, then sufficient conditions for FMNNs are derived. Additionally, an upper bound for the settling-time is estimated without the independence of the initial state. Through adjusting the FXTS controller, a less conservative estimation for the settling-time is presented, further achieving PTS. Notably, to improve control efficiency and cost, the designed controller is simplified to realize FXTS and PTS even with simpler construction. Finally, numerical simulations are conducted to validate the significant results obtained in this work. & COPY; 2023 Elsevier B.V. All rights reserved.
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