IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v425y2022ics0096300322001424.html
   My bibliography  Save this article

Event-Triggered μ-state estimation for Markovian jumping neural networks with mixed time-delays

Author

Listed:
  • Zou, Cong
  • Li, Bing
  • Liu, Feiyang
  • Xu, Bingrui

Abstract

In this paper, the issue of event-triggered μ-state estimation is addressed for a class of Markovian jumping neural networks (MJNNs) with mixed delays. The mixed delays involve both the infinitely distributed delay and the time-varying delay without requiring the upper bound, which has a distinction in existing conclusions and makes the model be more comprehensive. An event-triggered mechanism (ETM) with mode dependence is adopted to determine the appropriate updating instants of measurement outputs so as to alleviate the transmission of signals. By constructing a novel time-varying L-K functional with a general convergency rate and employing several analysis techniques, a sufficient criterion is obtained for ensuring the stochastic μ-stability performance of error system, which is a more general stability performance including exponential stability, power stability as well as logarithmic stability as its special cases. Finally, three numerical examples are listed to demonstrate the effectiveness of the proposed method.

Suggested Citation

  • Zou, Cong & Li, Bing & Liu, Feiyang & Xu, Bingrui, 2022. "Event-Triggered μ-state estimation for Markovian jumping neural networks with mixed time-delays," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    • Handle: RePEc:eee:apmaco:v:425:y:2022:i:c:s0096300322001424
    DOI: 10.1016/j.amc.2022.127056
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300322001424
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2022.127056?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Han, Xin-Xin & Wu, Kai-Ning & Ding, Xiaohua, 2020. "Finite-time stabilization for stochastic reaction-diffusion systems with Markovian switching via boundary control," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    2. Wu, Yongbao & Guo, Haihua & Li, Wenxue, 2020. "Finite-time stabilization of stochastic coupled systems on networks with Markovian switching via feedback control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. Xia, Weifeng & Xu, Shengyuan & Lu, Junwei & Li, Yongmin & Chu, Yuming & Zhang, Zhengqiang, 2021. "Event-triggered filtering for discrete-time Markovian jump systems with additive time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 391(C).
    4. Liu, Xiwei & Chen, Tianping, 2008. "Robust μ -stability for uncertain stochastic neural networks with unbounded time-varying delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2952-2962.
    5. Wang, Zengyun & Liu, Xinzhi, 2019. "Exponential stability of impulsive complex-valued neural networks with time delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 143-157.
    6. Shiwei Xia & Qian Zhang & Jiangping Jing & Zhaohao Ding & Jing Yu & Bing Chen & Haiwei Wu, 2019. "Distributed State Estimation of Multi-region Power System based on Consensus Theory," Energies, MDPI, vol. 12(5), pages 1-16, March.
    7. Yang, Xuan & Zhang, Xiao-Ping & Zhou, Suyang, 2012. "Coordinated algorithms for distributed state estimation with synchronized phasor measurements," Applied Energy, Elsevier, vol. 96(C), pages 253-260.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Xin & Cheng, Kaijie & Zhu, Liangkuan & Wei, Guoliang, 2023. "Outlier-resistant interval observer design for multirate time-delayed systems under the adaptive event-triggered protocols," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    2. Saravanan Shanmugam & Rajarathinam Vadivel & Nallappan Gunasekaran, 2023. "Finite-Time Synchronization of Quantized Markovian-Jump Time-Varying Delayed Neural Networks via an Event-Triggered Control Scheme under Actuator Saturation," Mathematics, MDPI, vol. 11(10), pages 1-24, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Xing-Yu & Wu, Kai-Ning & Liu, Xiao-Zhen, 2023. "Mittag–Leffler stabilization for short memory fractional reaction-diffusion systems via intermittent boundary control," Applied Mathematics and Computation, Elsevier, vol. 449(C).
    2. Cheng Peng & Jiaxin Ma & Qiankun Li & Shang Gao, 2022. "Noise-to-State Stability in Probability for Random Complex Dynamical Systems on Networks," Mathematics, MDPI, vol. 10(12), pages 1-11, June.
    3. Jiang, Tingting & Zhang, Yuping & Zeng, Yong & Zhong, Shouming & Shi, Kaibo & Cai, Xiao, 2021. "Finite-time analysis for networked predictive control systems with induced time delays and data packet dropouts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    4. Sun, Meng & Zhuang, Guangming & Xia, Jianwei & Wang, Yanqian & Chen, Guoliang, 2022. "Stochastic admissibility and H∞ output feedback control for singular Markov jump systems under dynamic measurement output event-triggered strategy," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    5. Cui, Kaiyan & Song, Zhanjie & Zhang, Shuo, 2022. "Stability of neutral-type neural network with Lévy noise and mixed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    6. Duan, Wenyong & Li, Yan & Sun, Yi & Chen, Jian & Yang, Xiaodong, 2020. "Enhanced master–slave synchronization criteria for chaotic Lur’e systems based on time-delayed feedback control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 177(C), pages 276-294.
    7. Zhang, Suhan & Gu, Wei & Qiu, Haifeng & Yao, Shuai & Pan, Guangsheng & Chen, Xiaogang, 2021. "State estimation models of district heating networks for integrated energy system considering incomplete measurements," Applied Energy, Elsevier, vol. 282(PA).
    8. Su, Hongzhi & Wang, Chengshan & Li, Peng & Li, Peng & Liu, Zhelin & Wu, Jianzhong, 2019. "Novel voltage-to-power sensitivity estimation for phasor measurement unit-unobservable distribution networks based on network equivalent," Applied Energy, Elsevier, vol. 250(C), pages 302-312.
    9. Zhao, Xin & Zeng, Zhijun, 2020. "Stationary distribution and extinction of a stochastic ratio-dependent predator–prey system with stage structure for the predator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    10. Tu, Zhengwen & Yang, Xinsong & Wang, Liangwei & Ding, Nan, 2019. "Stability and stabilization of quaternion-valued neural networks with uncertain time-delayed impulses: Direct quaternion method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    11. Zhang, Chunmei & Han, Bang-Sheng, 2020. "Stability analysis of stochastic delayed complex networks with multi-weights based on Razumikhin technique and graph theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    12. Das, Laya & Garg, Dinesh & Srinivasan, Babji, 2020. "NeuralCompression: A machine learning approach to compress high frequency measurements in smart grid," Applied Energy, Elsevier, vol. 257(C).
    13. Su, Hongzhi & Wang, Chengshan & Li, Peng & Liu, Zhelin & Yu, Li & Wu, Jianzhong, 2019. "Optimal placement of phasor measurement unit in distribution networks considering the changes in topology," Applied Energy, Elsevier, vol. 250(C), pages 313-322.
    14. Luis Vargas & Henrry Moyano, 2023. "A Novel Multi-Area Distribution State Estimation Approach with Nodal Redundancy," Energies, MDPI, vol. 16(10), pages 1-19, May.
    15. Pharunyou Chanthorn & Grienggrai Rajchakit & Jenjira Thipcha & Chanikan Emharuethai & Ramalingam Sriraman & Chee Peng Lim & Raja Ramachandran, 2020. "Robust Stability of Complex-Valued Stochastic Neural Networks with Time-Varying Delays and Parameter Uncertainties," Mathematics, MDPI, vol. 8(5), pages 1-19, May.
    16. Sriraman, R. & Cao, Yang & Samidurai, R., 2020. "Global asymptotic stability of stochastic complex-valued neural networks with probabilistic time-varying delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 103-118.
    17. Fan, Hongguang & Shi, Kaibo & Zhao, Yi, 2022. "Global μ-synchronization for nonlinear complex networks with unbounded multiple time delays and uncertainties via impulsive control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    18. Duan, Lian & Shi, Min & Huang, Chuangxia & Fang, Xianwen, 2021. "Synchronization in finite-/fixed-time of delayed diffusive complex-valued neural networks with discontinuous activations," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    19. Israa T. Aziz & Hai Jin & Ihsan H. Abdulqadder & Sabah M. Alturfi & Wisam H. Alobaidi & Firas M.F. Flaih, 2019. "T 2 S 2 G: A Novel Two-Tier Secure Smart Grid Architecture to Protect Network Measurements," Energies, MDPI, vol. 12(13), pages 1-24, July.
    20. Meng Xia & Dajun Du & Minrui Fei & Xue Li & Taicheng Yang, 2020. "A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids," Energies, MDPI, vol. 13(11), pages 1-19, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:425:y:2022:i:c:s0096300322001424. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.