IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v413y2022ics0096300321007207.html
   My bibliography  Save this article

Robust discrete-time non-smooth consensus protocol for multi-agent systems via super-twisting algorithm

Author

Listed:
  • Zhang, Weijian
  • Du, Haibo
  • Chu, Zhaobi

Abstract

In this paper, we firstly consider the consensus problems of first-order leaderless multi-agent systems with external disturbance. Then, we propose a robust discrete-time non-smooth (RDTNS) consensus protocol, which makes agents reach consensus within a region. Besides, we design a disturbance observer based on the discrete-time super-twisting algorithm (DTSTA), which can improve the disturbance rejection ability and decrease the consensus error for the multi-agent systems. At last, we get a robust discrete-time disturbance rejection control consensus protocol by combining the RDTNS consensus protocol with the discrete-time super-twisting observer (DTSTO). The simulation results verify the effectiveness of the proposed method.

Suggested Citation

  • Zhang, Weijian & Du, Haibo & Chu, Zhaobi, 2022. "Robust discrete-time non-smooth consensus protocol for multi-agent systems via super-twisting algorithm," Applied Mathematics and Computation, Elsevier, vol. 413(C).
  • Handle: RePEc:eee:apmaco:v:413:y:2022:i:c:s0096300321007207
    DOI: 10.1016/j.amc.2021.126636
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300321007207
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2021.126636?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. He, Xiaoyan & Wang, Qingyun, 2017. "Distributed finite-time leaderless consensus control for double-integrator multi-agent systems with external disturbances," Applied Mathematics and Computation, Elsevier, vol. 295(C), pages 65-76.
    2. Wang, Yingchun & Li, Haifeng & Qiu, Xiaojie & Xie, Xiangpeng, 2020. "Consensus tracking for nonlinear multi-agent systems with unknown disturbance by using model free adaptive iterative learning control," Applied Mathematics and Computation, Elsevier, vol. 365(C).
    3. Zhang, Yanhui & Liang, Hongjing & Ma, Hui & Zhou, Qi & Yu, Zhandong, 2018. "Distributed adaptive consensus tracking control for nonlinear multi-agent systems with state constraints," Applied Mathematics and Computation, Elsevier, vol. 326(C), pages 16-32.
    4. Zhao, Lin & Yu, Jinpeng & Lin, Chong & Yu, Haisheng, 2017. "Distributed adaptive fixed-time consensus tracking for second-order multi-agent systems using modified terminal sliding mode," Applied Mathematics and Computation, Elsevier, vol. 312(C), pages 23-35.
    5. Shao, Jinliang & Shi, Lei & Cao, Mengtao & Xia, Hong, 2018. "Distributed containment control for asynchronous discrete-time second-order multi-agent systems with switching topologies," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 47-59.
    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, Shenshen & Du, Haibo & Chen, Weile & Zhu, Wenwu, 2024. "Design of non-smooth consensus protocol for multi-agent systems under DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 463(C).

    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, Hongjie & Zhu, Yinglian & jing, Liu & ying, Wang, 2018. "Consensus of second-order delayed nonlinear multi-agent systems via node-based distributed adaptive completely intermittent protocols," Applied Mathematics and Computation, Elsevier, vol. 326(C), pages 1-15.
    2. Wang, Xin & Su, Housheng, 2019. "Consensus of hybrid multi-agent systems by event-triggered/self-triggered strategy," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 490-501.
    3. Zhu, Lin & Che, Wei-Wei & Jin, Xiao-Zheng, 2022. "Dynamic event-triggered tracking control for model-free networked control systems," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    4. Cai, Yuliang & Dai, Jing & Zhang, Huaguang & Wang, Yingchun, 2021. "Fixed-time leader-following/containment consensus of nonlinear multi-agent systems based on event-triggered mechanism," Applied Mathematics and Computation, Elsevier, vol. 396(C).
    5. Zhang, Xuxi & Liu, Xianping & Lewis, Frank L. & Wang, Xia, 2020. "Bipartite tracking consensus of nonlinear multi-agent systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    6. Gao, Shuo & Wen, Guoguang & Zhai, Xiaoqin & Zheng, Peng, 2023. "Finite-/fixed-time bipartite consensus for first-order multi-agent systems via impulsive control," Applied Mathematics and Computation, Elsevier, vol. 442(C).
    7. Li, Shenshen & Du, Haibo & Chen, Weile & Zhu, Wenwu, 2024. "Design of non-smooth consensus protocol for multi-agent systems under DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 463(C).
    8. Sharafian, Amin & Kanesan, Jeevan & Khairuddin, Anis Salwa Mohd & Ramanathan, Anand & Sharifi, Alireza & Bai, Xiaoshan, 2023. "A novel approach to state estimation of HIV infection dynamics using fixed-time fractional order observer," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    9. Long, Mingkang & Su, Housheng & Liu, Bo, 2019. "Second-order controllability of two-time-scale multi-agent systems," Applied Mathematics and Computation, Elsevier, vol. 343(C), pages 299-313.
    10. Yin, Zeyang & Luo, Jianjun & Wei, Caisheng, 2019. "Quasi fixed-time fault-tolerant control for nonlinear mechanical systems with enhanced performance," Applied Mathematics and Computation, Elsevier, vol. 352(C), pages 157-173.
    11. Fan, Ming-Can & Wu, Yue, 2018. "Global leader-following consensus of nonlinear multi-agent systems with unknown control directions and unknown external disturbances," Applied Mathematics and Computation, Elsevier, vol. 331(C), pages 274-286.
    12. Fu, Yingying & Li, Jing & Li, Xiaobo & Wu, Shuiyan, 2023. "Dynamic event-triggered adaptive control for uncertain stochastic nonlinear systems," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    13. Wang, Fang & Gao, Yali & Zhou, Chao & Zong, Qun, 2022. "Disturbance observer-based backstepping formation control of multiple quadrotors with asymmetric output error constraints," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    14. Cai, Yuliang & Zhang, Huaguang & Liu, Yang & He, Qiang, 2020. "Distributed bipartite finite-time event-triggered output consensus for heterogeneous linear multi-agent systems under directed signed communication topology," Applied Mathematics and Computation, Elsevier, vol. 378(C).
    15. 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).
    16. Kaviarasan, Boomipalagan & Kwon, Oh-Min & Park, Myeong Jin & Sakthivel, Rathinasamy, 2021. "Stochastic faulty estimator-based non-fragile tracking controller for multi-agent systems with communication delay," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    17. Feng, Hongyan & Xu, Huiling & Xu, Shengyuan & Chen, Weimin, 2019. "Model reference tracking control for spatially interconnected discrete-time systems with interconnected chains," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 50-62.
    18. Zhao, Huarong & Peng, Li & Yu, Hongnian, 2022. "Quantized model-free adaptive iterative learning bipartite consensus tracking for unknown nonlinear multi-agent systems," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    19. Zhao, Lin & Yu, Jinpeng & Lin, Chong & Yu, Haisheng, 2017. "Distributed adaptive fixed-time consensus tracking for second-order multi-agent systems using modified terminal sliding mode," Applied Mathematics and Computation, Elsevier, vol. 312(C), pages 23-35.
    20. Basheer, Ambreen & Rehan, Muhammad & Tufail, Muhammad & Razaq, Muhammad Ahsan, 2021. "A novel approach for adaptive H∞ leader-following consensus of higher-order locally Lipschitz multi-agent systems," Applied Mathematics and Computation, Elsevier, vol. 395(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:413:y:2022:i:c:s0096300321007207. 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.