Sampled-data-based exponential synchronization of switched coupled neural networks with unbounded delay

被引：19

作者：

Ge, Chao ^{[1
]}

Chang, Chenlei ^{[1
]}

Liu, Yajuan ^{[2
]}

Liu, Chengyuan ^{[1
]}

机构：

[1] North China Univ Sci & Technol, Coll Elect Engn, Tangshan 063000, Peoples R China

[2] North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2023年 / 117卷

关键词：

Neural networks; Bessel-Legendre inequality; Average dwell time; Lyapunov-Krasovskii functional; TIME-VARYING DELAYS; STABILITY ANALYSIS; PASSIVITY; SYSTEMS; MULTISYNCHRONIZATION; DISCRETE; CRITERIA; SUBJECT;

D O I：

10.1016/j.cnsns.2022.106931

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Based on sampled-data control, the exponential synchronization problem for a class of switched coupled neural networks with mixed delays is studied in the article. Considering the phenomena of mismatch between the controller and system, asyn-chronous switching occurs when switching signals appear in the sampling interval. Different from the existing results, the switched neural networks are based on coupling information. Then, an improved bilateral Lyapunov-Krasovskii functional is constructed, which involves more information. By using Bessel-Legendre inequality, some sufficient conditions for the exponential stability of synchronization error system are obtained by linear matrix inequalities. Average dwell time is obtained in the form of inequality that includes the maximum inter-event interval. Finally, two examples are used to illustrate the validity and feasibility of the proposed method.(c) 2022 Elsevier B.V. All rights reserved.

引用

页数：17

共 46 条

[1] Exponential Synchronization for Markovian Stochastic Coupled Neural Networks of Neutral-Type via Adaptive Feedback Control [J].

Chen, Huabin ;

Shi, Peng ;

Lim, Cheng-Chew .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 28 (07) :1618-1632

[2] Exponential quasi-synchronization of coupled delayed memristive neural networks via intermittent event-triggered control [J].

Chen, Jiejie ;

Chen, Boshan ;

Zeng, Zhigang .

NEURAL NETWORKS, 2021, 141 (141) :98-106

[3] Global exponential synchronization of high-order quaternion Hopfield neural networks with unbounded distributed delays and time-varying discrete delays [J].

Chen, Yonghui ;

Zhang, Xian ;

Xue, Yu .

MATHEMATICS AND COMPUTERS IN SIMULATION, 2022, 193 :173-189

[4]

Drogoul A, 2016, J DIFFER EQU, V270, P809

[5] Robust passivity analysis for uncertain neural networks with discrete and distributed time-varying delays [J].

Ge, Chao ;

Park, Ju H. ;

Hua, Changchun ;

Shi, Caijuan .

NEUROCOMPUTING, 2019, 364 :330-337

[6] Exponential synchronization of a class of neural networks with sampled-data control [J].

Ge, Chao ;

Wang, Bingfang ;

Wei, Xian ;

Liu, Yajuan .

APPLIED MATHEMATICS AND COMPUTATION, 2017, 315 :150-161

[7] Synchronization of Switched Neural Networks with Time-varying Delays via Sampled-data Control [J].

Han, Yuchen ;

Lian, Jie .

ASIAN JOURNAL OF CONTROL, 2019, 21 (03) :1260-1269

[8] Stability analysis for neural networks with time-varying interval delay [J].

He, Yong ;

Liu, G. P. ;

Rees, D. ;

Wu, Min .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2007, 18 (06) :1850-1854

[9] Semi-global/global output consensus for nonlinear multiagent systems with time delays [J].

Hua, Chang-Chun ;

Li, Kuo ;

Guan, Xin-Ping .

AUTOMATICA, 2019, 103 :480-489

[10] Smooth dynamic output feedback control for multiple time-delay systems with nonlinear uncertainties [J].

Hua, Chang-Chun ;

Guan, Xin-Ping .

AUTOMATICA, 2016, 68 :1-8

← 1 2 3 4 5 →