IDEAS home Printed from https://ideas.repec.org/a/hin/complx/6406179.html
   My bibliography  Save this article

Semiactive Nonsmooth Control for Building Structure with Deep Learning

Author

Listed:
  • Qing Wang
  • Jianhui Wang
  • Xiaofang Huang
  • Li Zhang

Abstract

Aiming at suppressing harmful effect for building structure by surface motion, semiactive nonsmooth control algorithm with Deep Learning is proposed. By finite-time stable theory, the building structure closed-loop system’s stability is discussed under the proposed control algorithm. It is found that the building structure closed-loop system is stable. Then the proposed control algorithm is applied on controlling the building structural vibration. The seismic action is chosen as El Centro seismic wave. Dynamic characteristics have comparative analysis between semiactive nonsmooth control and passive control in two simulation examples. They demonstrate that the designed control algorithm has great robustness and anti-interference. The proposed control algorithm is more effective than passive control in suppressing structural vibration.

Suggested Citation

  • Qing Wang & Jianhui Wang & Xiaofang Huang & Li Zhang, 2017. "Semiactive Nonsmooth Control for Building Structure with Deep Learning," Complexity, Hindawi, vol. 2017, pages 1-8, November.
    • Handle: RePEc:hin:complx:6406179
    DOI: 10.1155/2017/6406179
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2017/6406179.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2017/6406179.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2017/6406179?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. Francesco Smarra & Giovanni Domenico Di Girolamo & Vincenzo Gattulli & Fabio Graziosi & Alessandro D’Innocenzo, 2020. "Learning Models for Seismic-Induced Vibrations Optimal Control in Structures via Random Forests," Journal of Optimization Theory and Applications, Springer, vol. 187(3), pages 855-874, December.

    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:6406179. 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.