IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-3-030-10501-3_7.html
   My bibliography  Save this book chapter

Evidence-Based Robust Optimization of Pulsed Laser Orbital Debris Removal Under Epistemic Uncertainty

In: Modeling and Optimization in Space Engineering

Author

Listed:
  • Liqiang Hou

    (Xian Satellite Control Center)

  • Massimiliano Vasile

    (University of Strathclyde)

  • Zhaohui Hou

    (Beijing University of Posts and Telecommunications)

Abstract

An evidence-based robust optimization method for pulsed laser orbital debris removal (LODR) is presented. Epistemic type uncertainties due to limited knowledge are considered. The objective of the design optimization is set to minimize the debris lifetime while at the same time maximizing the corresponding belief value. The Dempster–Shafer theory of evidence (DST), which merges interval-based and probabilistic uncertainty modeling, is used to model and compute the uncertainty impacts. A Kriging based surrogate is used to reduce the cost due to the expensive numerical life prediction model. Effectiveness of the proposed method is illustrated by a set of benchmark problems. Based on the method, a numerical simulation of the removal of Iridium 33 with pulsed lasers is presented, and the most robust solutions with minimum lifetime under uncertainty are identified using the proposed method.

Suggested Citation

  • Liqiang Hou & Massimiliano Vasile & Zhaohui Hou, 2019. "Evidence-Based Robust Optimization of Pulsed Laser Orbital Debris Removal Under Epistemic Uncertainty," Springer Optimization and Its Applications, in: Giorgio Fasano & János D. Pintér (ed.), Modeling and Optimization in Space Engineering, pages 169-190, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-10501-3_7
    DOI: 10.1007/978-3-030-10501-3_7
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:spochp:978-3-030-10501-3_7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.