IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/1267380.html
   My bibliography  Save this article

Nonlinear Unknown Input Observer Based on Singular Value Decomposition Aided Reduced Dimension Cubature Kalman Filter

Author

Listed:
  • Wei Zhao
  • Huiguang Li
  • Liying Zou
  • Wenjuan Huang

Abstract

The paper presents a nonlinear unknown input observer (NUIO) based on singular value decomposition aided reduced dimension Cubature Kalman filter (SVDRDCKF) for a special class of nonlinear systems, the nonlinearity of which is only caused by part of its states. Firstly, the algorithm of general NUIO is discussed and the unknown input observer based on singular value decomposition aided Cubature Kalman filter (SVDCKF) given. Then a special nonlinear system model with unknown input is introduced. Based on the proposed model and the corresponding NUIO, the equivalent integral form with partial sampling and all sampling of the state vector in Cubature Kalman filter is analyzed. Finally the nonlinear unknown input observer based on singular value decomposition aided reduced dimension Cubature Kalman filter is obtained. Simulation results show that the proposed algorithm can meet the requirements of the system and is more important to increase the calculating efficiency a lot, although it has a decline in the accuracy of the filter.

Suggested Citation

  • Wei Zhao & Huiguang Li & Liying Zou & Wenjuan Huang, 2017. "Nonlinear Unknown Input Observer Based on Singular Value Decomposition Aided Reduced Dimension Cubature Kalman Filter," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-13, March.
    • Handle: RePEc:hin:jnlmpe:1267380
    DOI: 10.1155/2017/1267380
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2017/1267380.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2017/1267380.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2017/1267380?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. Zihao Lu & Na Wang & Shigui Dong, 2023. "Improved Square-Root Cubature Kalman Filtering Algorithm for Nonlinear Systems with Dual Unknown Inputs," Mathematics, MDPI, vol. 12(1), pages 1-28, 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:jnlmpe:1267380. 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.