IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-030-95157-3_14.html
   My bibliography  Save this book chapter

Data-Driven Identification of Rayleigh-Damped Second-Order Systems

In: Realization and Model Reduction of Dynamical Systems

Author

Listed:
  • Igor Pontes Duff

    (Max Planck Institute for Dynamics of Complex Technical Systems)

  • Pawan Goyal

    (Max Planck Institute for Dynamics of Complex Technical Systems)

  • Peter Benner

    (Max Planck Institute for Dynamics of Complex Technical Systems
    Technische Universität Chemnitz, Faculty of Mathematics)

Abstract

In this paper, we present a data-driven approach to identify second-order systems, having internal Rayleigh damping. This means that the damping matrix is given as a linear combination of the mass and stiffness matrices. These systems typically appear when performing various engineering studies, e.g., vibrational and structural analysis. In an experimental set-up, the frequency response of a system can be measured via various approaches, for instance, by measuring the vibrations using an accelerometer. As a consequence, given frequency samples, the identification of the underlying system relies on rational approximation. To that aim, we propose an identification of the corresponding second-order system, extending the Loewner framework for this class of systems. The efficiency of the proposed method is demonstrated by means of various numerical benchmarks.

Suggested Citation

  • Igor Pontes Duff & Pawan Goyal & Peter Benner, 2022. "Data-Driven Identification of Rayleigh-Damped Second-Order Systems," Springer Books, in: Christopher Beattie & Peter Benner & Mark Embree & Serkan Gugercin & Sanda Lefteriu (ed.), Realization and Model Reduction of Dynamical Systems, pages 255-272, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-95157-3_14
    DOI: 10.1007/978-3-030-95157-3_14
    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
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:sprchp:978-3-030-95157-3_14. 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.