IDEAS home Printed from https://ideas.repec.org/a/hin/complx/8382702.html
   My bibliography  Save this article

Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots

Author

Listed:
  • Xuejing Lan
  • Zhenghao Wu
  • Wenbiao Xu
  • Guiyun Liu

Abstract

This paper considers the region-based formation control for a swarm of robots with unknown nonlinear dynamics and disturbances. An adaptive neural network is designed to approximate the unknown nonlinear dynamics, and the desired formation shape is achieved by designing appropriate potential functions. Moreover, the collision avoidance, velocity consensus, and region tracking are all considered in the controller. The stability of the multirobot system has been demonstrated based on the Lyapunov theorem. Finally, three numerical simulations show the effectiveness of the proposed formation control scheme to deal with the narrow space, loss of robots, and formation merging problems.

Suggested Citation

  • Xuejing Lan & Zhenghao Wu & Wenbiao Xu & Guiyun Liu, 2018. "Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots," Complexity, Hindawi, vol. 2018, pages 1-8, December.
    • Handle: RePEc:hin:complx:8382702
    DOI: 10.1155/2018/8382702
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/8382702.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2018/8382702.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/8382702?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
    ---><---

    Citations

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


    Cited by:

    1. Junda Chen & Xuejing Lan & Ye Zhou & Jiaqiao Liang, 2022. "Formation Control with Connectivity Assurance for Missile Swarms by a Natural Co-Evolutionary Strategy," Mathematics, MDPI, vol. 10(22), pages 1-24, November.

    More about this item

    Statistics

    Access and download statistics

    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:hin:complx:8382702. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.