Least-Trimmed-Squares に基づく観測異常値を含む状態空間モデルの同定 Subspace Identification of State Space Models with Observation Outliers based on Least-Trimmed-Squares

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Author(s)

Abstract

In this paper, we consider a subspace system identification problem for linear stochastic systems subjected to observation outliers. First, the Least-Trimmed-Squares (LTS) technique due to Bai [1] is extended to Multiple-Input Multiple-Output (MIMO) regression model. Then, we identify the outliers in the output process of the MIMO state space model by using the LTS technique, and replace them by the median to obtain a preprocessed input-output data without outliers. We apply the Orthogonal (ORT) decomposition method to the preprocessed input-output data to get state space models. Numerical examples demonstrate the effectiveness of the proposed method.

Journal

  • Transactions of the Institute of Systems, Control and Information Engineers

    Transactions of the Institute of Systems, Control and Information Engineers 19(4), 157-165, 2006-04-15

    THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

References:  15

Codes

  • NII Article ID (NAID)
    10017534797
  • NII NACSIS-CAT ID (NCID)
    AN1013280X
  • Text Lang
    ENG
  • Article Type
    ART
  • ISSN
    13425668
  • NDL Article ID
    7876707
  • NDL Source Classification
    ZM11(科学技術--科学技術一般--制御工学)
  • NDL Call No.
    Z14-195
  • Data Source
    CJP  NDL  J-STAGE 
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