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An Improved Consistent Subspace Identification Method Using Parity Space for State-space Models

  • Jie HouEmail author
  • Fengwei Chen
  • Penghua Li
  • Zhiqin Zhu
  • Fei Liu
Article
  • 24 Downloads

Abstract

In this paper, an alternative consistent subspace identification method using parity space is proposed. The future/past input data and the past output data are used to construct the instrument variable to eliminate the noise effect on consistent estimation. The extended observability matrix and the triangular block-Toeplitz matrix are then retrieved from a parity space of the noise-free matrix using a singular value decomposition based method. The system matrices are finally estimated from the above estimated matrices. The consistency of the proposed method for estimation of the extended observability matrix and the triangular block-Toeplitz matrix is established. Compared with the classical SIMs using parity space like SIMPCA and SIMPCA-Wc, the proposed method generally enhances the estimated model efficiency/accuracy thanks to the use of future input data. Two examples are presented to illustrate the effectiveness and merit of the proposed method.

Keywords

Consistency instrumental variables parity space rank condition subspace identification 

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Copyright information

© ICROS, KIEE and Springer 2019

Authors and Affiliations

  • Jie Hou
    • 1
    Email author
  • Fengwei Chen
    • 2
  • Penghua Li
    • 1
  • Zhiqin Zhu
    • 1
  • Fei Liu
    • 3
  1. 1.College of AutomationChongqing University of Posts and TelecommunicationsChongqingChina
  2. 2.Department of AutomationWuhan UniversityWuhan, HubeiChina
  3. 3.National Robot Test and Assessment Center (Chongqing), Chongqing Dexin Robot Testing Center Co., LtdChongqingChina

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