IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v122y2016icp1-19.html
   My bibliography  Save this article

A fully adaptive rational global Arnoldi method for the model-order reduction of second-order MIMO systems with proportional damping

Author

Listed:
  • Bonin, Thomas
  • Faßbender, Heike
  • Soppa, Andreas
  • Zaeh, Michael

Abstract

The model order reduction of second-order dynamical multi-input and multi-output (MIMO) systems with proportional damping arising in the numerical simulation of mechanical structures is discussed. Based on finite element modelling the systems describing the mechanical structures are large and sparse, either undamped or proportionally damped. This work concentrates on a new model reduction algorithm for such second order MIMO systems which automatically generates a reduced system approximating the transfer function in the lower range of frequencies. The method is based on the rational global Arnoldi method. It determines the expansion points iteratively. The reduced order and the number of moments matched per expansion point are determined adaptively using a heuristic based on some error estimation. Numerical examples comparing our results to modal reduction and reduction via the rational block Arnoldi method are presented.

Suggested Citation

  • Bonin, Thomas & Faßbender, Heike & Soppa, Andreas & Zaeh, Michael, 2016. "A fully adaptive rational global Arnoldi method for the model-order reduction of second-order MIMO systems with proportional damping," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 122(C), pages 1-19.
    • Handle: RePEc:eee:matcom:v:122:y:2016:i:c:p:1-19
    DOI: 10.1016/j.matcom.2015.08.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475415001822
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2015.08.017?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chu, Chia-Chi & Lai, Ming-Hong & Feng, Wu-Shiung, 2008. "Model-order reductions for MIMO systems using global Krylov subspace methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(4), pages 1153-1164.
    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. Wang, Zhao-Hong & Jiang, Yao-Lin & Xu, Kang-Li, 2023. "Reduced-order state-space models for two-dimensional discrete systems via bivariate discrete orthogonal polynomials," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 212(C), pages 441-456.
    2. Li, Yanpeng & Jiang, Yaolin & Yang, Ping, 2021. "Time domain model order reduction of discrete-time bilinear systems with Charlier polynomials," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 905-920.

    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. Rydel, Marek & Stanisławski, Włodzimierz, 2017. "Selection of reduction parameters for complex plant MIMO LTI models using the evolutionary algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 140(C), pages 94-106.
    2. Li, Yanpeng & Jiang, Yaolin & Yang, Ping, 2021. "Time domain model order reduction of discrete-time bilinear systems with Charlier polynomials," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 905-920.
    3. Wang, Zhao-Hong & Jiang, Yao-Lin & Xu, Kang-Li, 2023. "Reduced-order state-space models for two-dimensional discrete systems via bivariate discrete orthogonal polynomials," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 212(C), pages 441-456.

    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:eee:matcom:v:122:y:2016:i:c:p:1-19. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.