IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v179y2024ics0960077924000262.html
   My bibliography  Save this article

Integrated L∞ anti-disturbance synchronization control for switched neural networks with unknown delays

Author

Listed:
  • Chang, Wenting
  • Sang, Hong
  • Guo, Liangdong
  • Wu, Libing
  • Dimirovski, Georgi M.

Abstract

This research is concerned with the integrated L∞ anti-disturbance synchronization control problem for continuous-time switched neural networks (SNNs). Different from the relevant synchronization results about SNNs, multiple disturbances and unknown delays are simultaneously addressed in a uniform framework. By constructing the novel Lyapunov function and the ameliorative combined switching strategy, an L∞ performance analysis framework with less conservativeness is then established, where each individual subnetwork is unnecessary to possess a prescribed L∞ performance index. By designing an appropriate disturbance observer and transforming the delay-dependent neuron activation function into a bounded disturbance, an integrated L∞ anti-disturbance synchronization control paradigm is also presented on the basis of the proposed analysis framework. Finally, three illustrative examples are employed to substantiate the applicability and superiority of the developed theoretical results.

Suggested Citation

  • Chang, Wenting & Sang, Hong & Guo, Liangdong & Wu, Libing & Dimirovski, Georgi M., 2024. "Integrated L∞ anti-disturbance synchronization control for switched neural networks with unknown delays," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    • Handle: RePEc:eee:chsofr:v:179:y:2024:i:c:s0960077924000262
    DOI: 10.1016/j.chaos.2024.114475
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077924000262
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2024.114475?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. Vadivel, R. & Hammachukiattikul, P. & Gunasekaran, Nallappan & Saravanakumar, R. & Dutta, Hemen, 2021. "Strict dissipativity synchronization for delayed static neural networks: An event-triggered scheme," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    2. Arik, Sabri, 2005. "Global robust stability analysis of neural networks with discrete time delays," Chaos, Solitons & Fractals, Elsevier, vol. 26(5), pages 1407-1414.
    3. Maharajan, C. & Raja, R. & Cao, Jinde & Rajchakit, G. & Alsaedi, Ahmed, 2018. "Novel results on passivity and exponential passivity for multiple discrete delayed neutral-type neural networks with leakage and distributed time-delays," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 268-282.
    4. Manivannan, R. & Samidurai, R. & Cao, Jinde & Alsaedi, Ahmed & Alsaadi, Fuad E., 2018. "Stability analysis of interval time-varying delayed neural networks including neutral time-delay and leakage delay," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 433-445.
    5. Karnan, A. & Nagamani, G., 2023. "Event-triggered extended dissipative synchronization for delayed neural networks with random uncertainties," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    6. Syed Ali, M. & Balasubramaniam, P., 2009. "Global exponential stability of uncertain fuzzy BAM neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2191-2199.
    Full references (including those not matched with items on IDEAS)

    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. Sang, Hong & Zhao, Ying & Wang, Peng & Wang, Yuzhong & Yu, Shuanghe & Dimirovski, Georgi M., 2023. "Finite-time peak-to-peak analysis for switched generalized neural networks comprised of finite-time unstable subnetworks," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    2. Xu, Jian & Chung, Kwok-Wai, 2009. "Dynamics for a class of nonlinear systems with time delay," Chaos, Solitons & Fractals, Elsevier, vol. 40(1), pages 28-49.
    3. 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).
    4. Sun, Yeong-Jeu, 2007. "Duality between observation and output feedback for linear systems with multiple time delays," Chaos, Solitons & Fractals, Elsevier, vol. 33(3), pages 879-884.
    5. Alsaedi, Ahmed & Cao, Jinde & Ahmad, Bashir & Alshehri, Ahmed & Tan, Xuegang, 2022. "Synchronization of master-slave memristive neural networks via fuzzy output-based adaptive strategy," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    6. Yang, Wei & Cui, Guozeng & Ma, Qian & Ma, Jiali & Tao, Chongben, 2022. "Finite-time adaptive event-triggered command filtered backstepping control for a QUAV," Applied Mathematics and Computation, Elsevier, vol. 423(C).
    7. Duan, Lian & Liu, Jinzhi & Huang, Chuangxia & Wang, Zengyun, 2022. "Finite-/fixed-time anti-synchronization of neural networks with leakage delays under discontinuous disturbances," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    8. Liu, Haoliang & Zhang, Taixiang & Li, Xiaodi, 2021. "Event-triggered control for nonlinear systems with impulse effects," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    9. R. Sakthivel & R. Raja & S. M. Anthoni, 2013. "Exponential Stability for Delayed Stochastic Bidirectional Associative Memory Neural Networks with Markovian Jumping and Impulses," Journal of Optimization Theory and Applications, Springer, vol. 158(1), pages 251-273, July.
    10. Syed Ali, M. & Narayanan, Govindasamy & Shekher, Vineet & Alsulami, Hamed & Saeed, Tareq, 2020. "Dynamic stability analysis of stochastic fractional-order memristor fuzzy BAM neural networks with delay and leakage terms," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    11. Adhira, B. & Nagamani, G., 2023. "Exponentially finite-time dissipative discrete state estimator for delayed competitive neural networks via semi-discretization approach," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    12. Lv, Jian Cheng & Yi, Zhang, 2007. "Convergence analysis of Chauvin’s PCA learning algorithm with a constant learning rate," Chaos, Solitons & Fractals, Elsevier, vol. 32(4), pages 1562-1571.
    13. Li, Chuandong & Chen, Jinyu & Huang, Tingwen, 2007. "A new criterion for global robust stability of interval neural networks with discrete time delays," Chaos, Solitons & Fractals, Elsevier, vol. 31(3), pages 561-570.
    14. Gau, R.S. & Lien, C.H. & Hsieh, J.G., 2007. "Global exponential stability for uncertain cellular neural networks with multiple time-varying delays via LMI approach," Chaos, Solitons & Fractals, Elsevier, vol. 32(4), pages 1258-1267.
    15. Zhou, Xiaobing & Wu, Yue & Li, Yi & Yao, Xun, 2009. "Stability and Hopf bifurcation analysis on a two-neuron network with discrete and distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 40(3), pages 1493-1505.
    16. Ye, Zhiyong & Zhang, He & Zhang, Hongyu & Zhang, Hua & Lu, Guichen, 2015. "Mean square stabilization and mean square exponential stabilization of stochastic BAM neural networks with Markovian jumping parameters," Chaos, Solitons & Fractals, Elsevier, vol. 73(C), pages 156-165.
    17. Rajchakit, G. & Sriraman, R. & Lim, C.P. & Unyong, B., 2022. "Existence, uniqueness and global stability of Clifford-valued neutral-type neural networks with time delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 508-527.
    18. Liu, Yang & Zhang, Zhenzhen & Chen, Hao & Zhong, Shouming, 2023. "A memory behavior related hybrid event-triggered mechanism for an improved robust control on neural networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 212(C), pages 1-20.
    19. Mak, K.L. & Peng, J.G. & Xu, Z.B. & Yiu, K.F.C., 2007. "A new stability criterion for discrete-time neural networks: Nonlinear spectral radius," Chaos, Solitons & Fractals, Elsevier, vol. 31(2), pages 424-436.
    20. Luo, Mei & Wang, JinRong & Meng, Deyuan, 2023. "Stochastic convergence problems on switching networks: An event-triggered method," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).

    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:chsofr:v:179:y:2024:i:c:s0960077924000262. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.