IDEAS home Printed from https://ideas.repec.org/a/hin/complx/9098151.html
   My bibliography  Save this article

Improved Hybrid Fireworks Algorithm-Based Parameter Optimization in High-Order Sliding Mode Control of Hypersonic Vehicles

Author

Listed:
  • Xiaomeng Yin
  • Xing Wei
  • Lei Liu
  • Yongji Wang

Abstract

With respect to the nonlinear hypersonic vehicle (HV) dynamics, achieving a satisfactory tracking control performance under uncertainties is always a challenge. The high-order sliding mode control (HOSMC) method with strong robustness has been applied to HVs. However, there are few methods for determining suitable HOSMC parameters for an efficacious control of HV, given that the uncertainties are randomly distributed. In this study, we introduce a hybrid fireworks algorithm- (FWA-) based parameter optimization into HV control design to satisfy the design requirements with high probability. First, the complex relation between design parameters and the cost function that evaluates the likelihood of system instability and violation of design requirements is modeled via stochastic robustness analysis. Subsequently, we propose an efficient hybrid FWA to solve the complex optimization problem concerning the uncertainties. The efficiency of the proposed hybrid FWA-based optimization method is demonstrated in the search of the optimal HV controller, in which the proposed method exhibits a better performance when compared with other algorithms.

Suggested Citation

  • Xiaomeng Yin & Xing Wei & Lei Liu & Yongji Wang, 2018. "Improved Hybrid Fireworks Algorithm-Based Parameter Optimization in High-Order Sliding Mode Control of Hypersonic Vehicles," Complexity, Hindawi, vol. 2018, pages 1-16, March.
  • Handle: RePEc:hin:complx:9098151
    DOI: 10.1155/2018/9098151
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/9098151.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/8503/2018/9098151.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2018/9098151?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
    ---><---

    References listed on IDEAS

    as
    1. Adel Taieb & Moêz Soltani & Abdelkader Chaari, 2017. "Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO," Complexity, Hindawi, vol. 2017, pages 1-11, October.
    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. Lin Sun & Suisui Chen & Jiucheng Xu & Yun Tian, 2019. "Improved Monarch Butterfly Optimization Algorithm Based on Opposition-Based Learning and Random Local Perturbation," Complexity, Hindawi, vol. 2019, pages 1-20, February.
    2. LiuQing Yang & YanBin Liu & Yong Zhang, 2019. "Nonlinear Trajectory Controller with Improved Performances for Waveriders," Complexity, Hindawi, vol. 2019, pages 1-16, March.

    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. Qu, Jingguo & Zhang, Zilong & Zhang, Huiqi, 2019. "An improved predictive control model for stochastic max-plus-linear systems," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 210-218.

    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:9098151. 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: 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.