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Orthogonal projection based subspace identification against colored noise

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Abstract

In this paper, a bias-eliminated subspace identification method is proposed for industrial applications subject to colored noise. Based on double orthogonal projections, an identification algorithm is developed to eliminate the influence of colored noise for consistent estimation of the extended observability matrix of the plant state-space model. A shift-invariant approach is then given to retrieve the system matrices from the estimated extended observability matrix. The persistent excitation condition for consistent estimation of the extended observability matrix is analyzed. Moreover, a numerical algorithm is given to compute the estimation error of the estimated extended observability matrix. Two illustrative examples are given to demonstrate the effectiveness and merit of the proposed method.

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Authors and Affiliations

  1. School of Control Science and Engineering, Dalian University of Technology, Dalian Liaoning, 116024, China

    Jie Hou, Tao Liu & Fengwei Chen

Authors
  1. Jie Hou
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  2. Tao Liu
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  3. Fengwei Chen
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Corresponding author

Correspondence to Tao Liu.

Additional information

This work was supported by the National Thousand Talents Program of China, the National Natural Science Foundation of China (Nos. 61473054, 61633006), and the Fundamental Research Funds for the Central Universities of China (No. DUT15ZD108).

Jie HOU received the B.Eng. degree in Automation from Beifang University of Nationalities, Yinchuan, China, in 2010, the M.Sc. degree in Control Science and Engineering from Chongqing University, Chongqing, China, in 2013. He is currently a Ph.D. candidate in the School of Control Science and Engineering, Dalian University of Technology. His research interest covers system identification.

Tao LIU received his Ph.D. degree in Control Science and Engineering from Shanghai Jiaotong University, Shanghai, China, in 2006. He is a professor in the Institute of Advanced Control Technology at Dalian University of Technology. His research interests include chemical and industrial process identification & modeling, robust process control, iterative learning control, batch process optimization. He is a member of the Technical Committee on Chemical Process Control of IFAC, Technical Committee on System Identification and Adaptive Control of the IEEE Control System Society, and Chinese Process Control Committee.

Fengwei CHEN received the B.Eng. and M.Eng. degrees from Wuhan University, Wuhan, China, in 2009 and 2011, respectively, and the Ph.D. degree from Université de Lorraine, Nancy, France, in 2014. He is currently working with Dalian University of Technology, Dalian, China. His research interests include system identification and signal processing.

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Hou, J., Liu, T. & Chen, F. Orthogonal projection based subspace identification against colored noise. Control Theory Technol. 15, 69–77 (2017). https://doi.org/10.1007/s11768-017-6003-7

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  • DOI: https://doi.org/10.1007/s11768-017-6003-7

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