Finite-time Synchronization of Delayed Semi-Markov Neural Networks with Dynamic Event-triggered Scheme

被引：0
|
作者：
Yujing Jin
Wenhai Qi
Guangdeng Zong
机构：
[1] Qufu Normal University,School of Engineering
[2] Chengdu University,School of Information Science and Engineering
来源：
International Journal of Control, Automation and Systems | 2021年 / 19卷
关键词：
Dynamic event-triggered scheme; finite-time synchronization; Lyapunov-Krasovskii functional; semi-Markov neural networks;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, the finite-time synchronization (FTS) of semi-Markov neural networks (S-MNNs) with time-varying delay is presented. According to the Lyapunov stability theory, a mode-dependent Lyapunov-Krasovskii functional (LKF) is constructed. Compared with the traditional static event triggered scheme (ETS), a dynamic ETS is adopted to adjust the amount of data transmission and reduce the network burden. By using the general free-weighting matrix method (F-WMM) to estimate a single integral term, a less conservative conclusion is proposed in standard linear matrix inequalities (LMIs). Finally, under the comparison of the static ETS and the dynamic ETS, a simulation example verifies the superiority of this method.
引用
收藏
页码：2297 / 2308
页数：11
相关论文
共 50 条
  • [1] Finite-time Synchronization of Delayed Semi-Markov Neural Networks with Dynamic Event-triggered Scheme
    Jin, Yujing
    Qi, Wenhai
    Zong, Guangdeng
    INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2021, 19 (06) : 2297 - 2308
  • [2] Finite-time synchronization for complex dynamic networks with semi-Markov switching topologies: An H∞ event-triggered control scheme
    Wang, Jing
    Ru, Tingting
    Xia, Jianwei
    Wei, Yunhang
    Wang, Zhen
    APPLIED MATHEMATICS AND COMPUTATION, 2019, 356 : 235 - 251
  • [3] Synchronization for stochastic semi-Markov jump neural networks with dynamic event-triggered scheme
    Cao, Dianguo
    Jin, Yujing
    Qi, Wenhai
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2023, 360 (16): : 12620 - 12639
  • [4] Event-triggered finite-time quantized synchronization of uncertain delayed neural networks
    Zhang, Yingqi
    Li, Xiao
    Liu, Caixia
    OPTIMAL CONTROL APPLICATIONS & METHODS, 2022, 43 (06): : 1584 - 1603
  • [5] Event-triggered finite-time synchronization for uncertain neural networks with quantizations
    Yingqi Zhang
    Xiao Li
    Jingjing Yan
    Computational and Applied Mathematics, 2022, 41
  • [6] Event-triggered synchronization for semi-Markov jump complex dynamic networks with time-varying delay
    Zheng, Cheng-De
    Liu, Shengzhou
    Meng, Haorui
    NEUROCOMPUTING, 2021, 458 : 390 - 402
  • [7] Event-triggered finite-time synchronization for uncertain neural networks with quantizations
    Zhang, Yingqi
    Li, Xiao
    Yan, Jingjing
    COMPUTATIONAL & APPLIED MATHEMATICS, 2022, 41 (05):
  • [8] Guaranteed cost finite-time control for semi-Markov jump systems with event-triggered scheme and quantization input
    Zong, Guangdeng
    Ren, Hangli
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2019, 29 (15) : 5251 - 5273
  • [9] Finite-time H∞ synchronization control for semi-Markov jump delayed neural networks with randomly occurring uncertainties
    Li, Feng
    Shen, Hao
    NEUROCOMPUTING, 2015, 166 : 447 - 454
  • [10] Synchronization for singular neural networks with finite time characteristic under event-triggered scheme
    Wu, Yifan
    Zhu, Jingjuan
    Pang, Yujing
    Fu, Yanran
    Hao, Mengjuan
    Meng, Yanan
    Zhuang, Guangming
    2024 3RD CONFERENCE ON FULLY ACTUATED SYSTEM THEORY AND APPLICATIONS, FASTA 2024, 2024, : 831 - 836
12345