Closed-Loop Subspace Identification Algorithm of EIV Model Based on Orthogonal Decomposition and PCA

  • Jianguo Wang
  • Yong Guo
  • Juanjuan Wang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 323)


In this paper, after analysis of the reason why some existing subspace methods may deliver a bias in the closed-loop conditions, a new SIM for closed-loop system based on orthogonal decomposition and principal component analysis is proposed by adopting the EIV model structure. Then, the underlying reason why SIMPCA-Wc delivers a bias estimate is explained from realization theory of closed-loop system based on orthogonal decomposition. At last, simulations show that the proposed method ORT_PCA-Wc used for closed-loop EIV system is effective and feasible.


subspace identification methods (SIMs) closed-loop identification orthogonal decomposition principal component analysis (PCA) error in variable (EIV) 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jianguo Wang
    • 1
  • Yong Guo
    • 1
  • Juanjuan Wang
    • 1
  1. 1.Department of Automation, School of Mechatronics Engineering and Automation, Shanghai Key Laboratory of Power Station Automation TechnologyShanghai UniversityShanghaiChina

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