IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v464y2024ics0096300323005696.html
   My bibliography  Save this article

Practical time-boundary consensus for fractional-order multi-agent systems under well-known and estimable topology

Author

Listed:
  • Qing, Nengneng
  • Yang, Yongqing
  • Luan, Xiaoli
  • Wan, Haiying

Abstract

A framework for multi-agent systems with single-integrator dynamics to achieve practical fixed-time consensus has been developed under a well-known topology. However, the disagreement boundary in which is influenced by the initial values of the system. To avoid this, a practical time-boundary (PTB) consensus framework using a novel time-boundary-base generator (TBBG) is proposed in this paper, and it is extended to fractional-order multi-agent systems and estimable topology. A significant fractional differential equation is solved as the theoretical basis to achieve PTB consensus. Evolving from the time-base generator, this novel TBBG inherits the benefit of reducing the initial control input and saves energy consumption by optimizing four newly added adjustable parameters compared to the existing work. Additionally, outcomes are extended to quasi-PTB consensus and PTB-cluster consensus. The effectiveness and superiorities of the proposed approach are illustrated by two numerical examples.

Suggested Citation

  • Qing, Nengneng & Yang, Yongqing & Luan, Xiaoli & Wan, Haiying, 2024. "Practical time-boundary consensus for fractional-order multi-agent systems under well-known and estimable topology," Applied Mathematics and Computation, Elsevier, vol. 464(C).
    • Handle: RePEc:eee:apmaco:v:464:y:2024:i:c:s0096300323005696
    DOI: 10.1016/j.amc.2023.128400
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300323005696
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2023.128400?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. Du, Feifei & Lu, Jun-Guo, 2021. "New criterion for finite-time synchronization of fractional order memristor-based neural networks with time delay," Applied Mathematics and Computation, Elsevier, vol. 389(C).
    2. Fan, Yanyan & Jin, Zhenlin & Luo, Xiaoyuan & Guo, Baosu, 2022. "Robust finite-time consensus control for Euler–Lagrange multi-agent systems subject to switching topologies and uncertainties," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    3. Wu, Zhengtian & Gao, Qing & Jiang, Baoping & Karimi, Hamid Reza, 2021. "Solving the production transportation problem via a deterministic annealing neural network method," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    4. Huang, Jingyang & Jia, Wei & Wan, Tongxin & Xiao, Shuyi & Wang, Liqi & Dong, Jiuxiang, 2023. "Adaptive event-triggered fault-tolerant consensus of linear heterogeneous multiagent systems via hierarchical approach," Applied Mathematics and Computation, Elsevier, vol. 447(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. Zhen Yang & Zhengqiu Zhang, 2022. "Finite-Time Synchronization Analysis for BAM Neural Networks with Time-Varying Delays by Applying the Maximum-Value Approach with New Inequalities," Mathematics, MDPI, vol. 10(5), pages 1-16, March.
    2. Zhang, Zhe & Wang, Yaonan & Zhang, Jing & Ai, Zhaoyang & Liu, Feng, 2022. "Novel stability results of multivariable fractional-order system with time delay," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    3. He, Jin-Man & Pei, Li-Jun, 2023. "Function matrix projection synchronization for the multi-time delayed fractional order memristor-based neural networks with parameter uncertainty," Applied Mathematics and Computation, Elsevier, vol. 454(C).
    4. Luo, Danfeng & Tian, Mengquan & Zhu, Quanxin, 2022. "Some results on finite-time stability of stochastic fractional-order delay differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    5. Du, Feifei & Lu, Jun-Guo, 2021. "New approach to finite-time stability for fractional-order BAM neural networks with discrete and distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    6. Cui, Qian & Li, Lulu & Lu, Jianquan & Alofi, Abdulaziz, 2022. "Finite-time synchronization of complex dynamical networks under delayed impulsive effects," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    7. Du, Feifei & Lu, Jun-Guo, 2021. "Explicit solutions and asymptotic behaviors of Caputo discrete fractional-order equations with variable coefficients," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    8. Shuang Wang & Hai Zhang & Weiwei Zhang & Hongmei Zhang, 2021. "Finite-Time Projective Synchronization of Caputo Type Fractional Complex-Valued Delayed Neural Networks," Mathematics, MDPI, vol. 9(12), pages 1-14, June.
    9. Sinha, Ankur & Das, Arka & Anand, Guneshwar & Jayaswal, Sachin, 2023. "A general purpose exact solution method for mixed integer concave minimization problems," European Journal of Operational Research, Elsevier, vol. 309(3), pages 977-992.
    10. Tian, Yongjie & Zhang, Huiyan & Liu, Yongchao & Zhao, Ning & Mathiyalagan, Kalidass, 2024. "Event-triggered adaptive secure tracking control for nonlinear cyber–physical systems against unknown deception attacks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 221(C), pages 79-93.
    11. Yan, Hongyun & Qiao, Yuanhua & Duan, Lijuan & Miao, Jun, 2022. "New results of quasi-projective synchronization for fractional-order complex-valued neural networks with leakage and discrete delays," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    12. Long, Changqing & Zhang, Guodong & Hu, Junhao, 2021. "Fixed-time synchronization for delayed inertial complex-valued neural networks," Applied Mathematics and Computation, Elsevier, vol. 405(C).
    13. Yu, Peilin & Deng, Feiqi, 2022. "Stabilization analysis of Markovian asynchronous switched systems with input delay and Lévy noise," Applied Mathematics and Computation, Elsevier, vol. 422(C).
    14. Li, Xuemei & Liu, Xinge & Wang, Fengxian, 2023. "Anti-synchronization of fractional-order complex-valued neural networks with a leakage delay and time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    15. Zhu, Fanglai & Du, Wenqing, 2024. "Observer-based consensus of multi-agent systems under odd distributed impulsive control protocol," Applied Mathematics and Computation, Elsevier, vol. 466(C).
    16. Yang, Zhanying & Zhang, Jie & Zhang, Zhihui & Mei, Jun, 2023. "An improved criterion on finite-time stability for fractional-order fuzzy cellular neural networks involving leakage and discrete delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 910-925.
    17. Yi, Jiale, 2023. "Adaptive fuzzy connectivity-preserving consensus protocols for stochastic strict-feedback nonlinear MASs subject to unmeasured periodic disturbances," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    18. Ning, Jinghua & Hua, Changchun, 2022. "H∞ output feedback control for fractional-order T-S fuzzy model with time-delay," Applied Mathematics and Computation, Elsevier, vol. 416(C).
    19. Li, Hong-Li & Hu, Cheng & Zhang, Long & Jiang, Haijun & Cao, Jinde, 2021. "Non-separation method-based robust finite-time synchronization of uncertain fractional-order quaternion-valued neural networks," Applied Mathematics and Computation, Elsevier, vol. 409(C).
    20. Chen, Yuting & Li, Xiaoyan & Liu, Song, 2021. "Finite-time stability of ABC type fractional delay difference equations," Chaos, Solitons & Fractals, Elsevier, vol. 152(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:apmaco:v:464:y:2024:i:c:s0096300323005696. 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.