IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i17p2096-d625083.html
   My bibliography  Save this article

Structure Identification of Fractional-Order Dynamical Network with Different Orders

Author

Listed:
  • Mingcong Zhou

    (School of Mathematics and Statistics, Jiangxi Normal University, Nanchang 330022, China)

  • Zhaoyan Wu

    (School of Mathematics and Statistics, Jiangxi Normal University, Nanchang 330022, China)

Abstract

Topology structure and system parameters have a great influence on the dynamical behavior of dynamical networks. However, they are sometimes unknown or uncertain in advance. How to effectively identify them has been investigated in various network models, from integer-order networks to fractional-order networks with the same order. In the real world, many systems consist of subsystems with different fractional orders. Therefore, the structure identification of a dynamical network with different fractional orders is investigated in this paper. Through designing proper adaptive controllers and parameter updating laws, two network estimators are well constructed. One is for identifying only the unknown topology structure. The other is for identifying both the unknown topology structure and system parameters. Based on the Lyapunov function method and the stability theory of fractional-order dynamical systems, the theoretical results are analytically proved. The effectiveness is verified by three numerical examples as well. In addition, the designed estimators have a good performance in monitoring switching topology. From the practical viewpoint, the designed estimators can be used to monitor the change of current and voltage in the fractional-order circuit systems.

Suggested Citation

  • Mingcong Zhou & Zhaoyan Wu, 2021. "Structure Identification of Fractional-Order Dynamical Network with Different Orders," Mathematics, MDPI, vol. 9(17), pages 1-11, August.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:17:p:2096-:d:625083
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/17/2096/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/17/2096/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Du, Hongyue, 2019. "Modified function projective synchronization between two fractional-order complex dynamical networks with unknown parameters and unknown bounded external disturbances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    2. Li, Hong-Li & Cao, Jinde & Jiang, Haijun & Alsaedi, Ahmed, 2019. "Finite-time synchronization and parameter identification of uncertain fractional-order complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    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. Zhou, Wenjia & Hu, Yuanfa & Liu, Xiaoyang & Cao, Jinde, 2022. "Finite-time adaptive synchronization of coupled uncertain neural networks via intermittent control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    2. Huang, Conggui & Wang, Fei & Zheng, Zhaowen, 2021. "Exponential stability for nonlinear fractional order sampled-data control systems with its applications," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    3. Huang, Chengdai & Liu, Heng & Chen, Xiaoping & Cao, Jinde & Alsaedi, Ahmed, 2020. "Extended feedback and simulation strategies for a delayed fractional-order control system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    4. Liu, Xinmiao & Xia, Jianwei & Huang, Xia & Shen, Hao, 2020. "Generalized synchronization for coupled Markovian neural networks subject to randomly occurring parameter uncertainties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    5. Dawei Ding & Ya Wang & Yongbing Hu & Zongli Yang & Hongwei Zhang & Xu Zhang, 2022. "Pinning synchronization and parameter identification of fractional-order complex-valued dynamical networks with multiple weights," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(8), pages 1-12, August.
    6. Mao, Kun & Liu, Xiaoyang & Cao, Jinde & Hu, Yuanfa, 2022. "Finite-time bipartite synchronization of coupled neural networks with uncertain parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    7. Aadhithiyan, S. & Raja, R. & Zhu, Q. & Alzabut, J. & Niezabitowski, M. & Lim, C.P., 2021. "Modified projective synchronization of distributive fractional order complex dynamic networks with model uncertainty via adaptive control," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    8. Weiqiu Pan & Tianzeng Li & Muhammad Sajid & Safdar Ali & Lingping Pu, 2022. "Parameter Identification and the Finite-Time Combination–Combination Synchronization of Fractional-Order Chaotic Systems with Different Structures under Multiple Stochastic Disturbances," Mathematics, MDPI, vol. 10(5), pages 1-26, February.

    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:gam:jmathe:v:9:y:2021:i:17:p:2096-:d:625083. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.