Pinning event-triggered sampled-data synchronization of coupled reaction-diffusion neural networks

被引:4
作者
Zhao, Feng-Liang [1 ]
Wang, Zi-Peng [2 ]
Qiao, Junfei [2 ]
Wu, Huai-Ning [3 ]
Huang, Tingwen [4 ]
机构
[1] Sun Yat Sen Univ, Sch Intelligent Syst Engn, Shenzhen Campus, Shenzhen 518000, Peoples R China
[2] Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
[3] Beihang Univ, Sch Automat Sci & Elect Engn, Sci & Technol Aircraft Control Lab, Beijing, Peoples R China
[4] Texas A&M Univ, Sci Program, College Stn, TX USA
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Coupled reaction-diffusion neural networks; (CRDNNs); Pinning event-triggered sampled-data (PETSD); control; Synchronization; Spatially point measurements; TIME-VARYING DELAYS; INFINITY OUTPUT SYNCHRONIZATION; SYSTEMS; STABILIZATION; STABILITY; TERMS;
D O I
10.1016/j.neucom.2024.128028
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, the synchronization problem of coupled reaction-diffusion neural networks (CRDNNs) is considered by using pinning event -triggered sampled -data (PETSD) control method under spatially point measurements. To save the limited transmission channel, a PETSD control mechanism by controlling a small fraction of the nodes is proposed to decrease the update frequency of controller and the unnecessary SD. Then, based on the Lyapunov-Krasovskii functional (LKF) and inequality techniques, sufficient conditions for exponential stability of the synchronization error system presented by linear matrix inequalities (LMIs) can be derived through the designed PETSD controller. Finally, simulation results of one numerical example are presented to demonstrate the effectiveness of the proposed design approach.
引用
收藏
页数:9
相关论文
共 50 条
[31]   Finite-time event-triggered synchronization for reaction-diffusion complex networks [J].
Wang, Aijuan ;
Liao, Xiaofeng ;
Dong, Tao .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2018, 509 :111-120
[32]   Quantized Sampled-Data Synchronization of Delayed Reaction-Diffusion Neural Networks Under Spatially Point Measurements [J].
Wang, Zi-Peng ;
Wu, Huai-Ning ;
Wang, Jin-Liang ;
Li, Han-Xiong .
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 51 (12) :5740-5751
[33]   Time-space sampled-data control for semi-Markov reaction-diffusion neural networks: Adopting multiple event-triggered protocols [J].
Wei, Wanying ;
Zhang, Bin ;
Cheng, Jun ;
Cao, Jinde ;
Zhang, Dan ;
Yan, Huaicheng .
INFORMATION SCIENCES, 2025, 698
[34]   Pinning Control for Synchronization of Coupled Reaction-Diffusion Neural Networks With Directed Topologies [J].
Wang, Jin-Liang ;
Wu, Huai-Ning ;
Huang, Tingwen ;
Ren, Shun-Yan ;
Wu, Jigang .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2016, 46 (08) :1109-1120
[35]   Synchronization for hybrid coupled reaction-diffusion neural networks with stochastic disturbances via spatial sampled-data control strategy [J].
Song, Xiaona ;
Li, Xingru ;
Ning, Zhaoke ;
Wang, Mi ;
Man, Jingtao .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 2021, 235 (10) :1762-1776
[36]   Event-triggered passivity and synchronization of delayed multiple-weighted coupled reaction-diffusion neural networks with non-identical nodes [J].
Lin, Shanrong ;
Huang, Yanli ;
Ren, Shunyan .
NEURAL NETWORKS, 2020, 121 :259-275
[37]   Adaptive event-triggered extended dissipative synchronization of delayed reaction-diffusion neural networks under deception attacks [J].
Zhao, Feng-Liang ;
Wang, Zi-Peng ;
Qiao, Junfei ;
Wu, Huai-Ning ;
Huang, Tingwen .
NEURAL NETWORKS, 2023, 166 :366-378
[38]   Event-triggered H?/passive synchronization for Markov jumping reaction-diffusion neural networks under deception attacks [J].
Zhang, Ziwei ;
Li, Feng ;
Fang, Ting ;
Shi, Kaibo ;
Shen, Hao .
ISA TRANSACTIONS, 2022, 129 :36-43
[39]   H∞ synchronization of coupled reaction-diffusion neural networks with mixed delays [J].
He, Ping ;
Li, Yangmin .
COMPLEXITY, 2016, 21 (S2) :42-53
[40]   Adaptive smooth sampled-data control for synchronization of T-S fuzzy reaction-diffusion neural networks with actuator saturation [J].
Niu, Yuchen ;
Shi, Kaibo ;
Cai, Xiao ;
Wen, Shiping .
AIMS MATHEMATICS, 2025, 10 (01) :1142-1161