Recursive subspace identification approach of a closed-loop model

A subspace model identification algorithm under closed-loop experimental condition is presented in this paper that can be implemented to recursively identify and update system model. A new updating scheme is developed to obtain the projected data matrix recursively through sliding window technique and linear equation. Based on the propagator type method in array signal processing, the subspace spanned by the column vectors of the extended observability matrix is estimated without singular values decomposition. The proposed method is feasible for the closed-loop system contaminated with colored noises. The numerical example shows the effectiveness of the proposed algorithm.

[1]  Alessandro Chiuso,et al.  Consistency analysis of some closed-loop subspace identification methods , 2005, Autom..

[2]  Giorgio Picci,et al.  Subspace identification of closed loop systems by the orthogonal decomposition method , 2005, Autom..

[3]  Bart De Moor,et al.  Subspace Identification for Linear Systems: Theory ― Implementation ― Applications , 2011 .

[4]  Marion Gilson,et al.  SUBSPACE-BASED OPTIMAL IV METHOD FOR CLOSED-LOOP SYSTEM IDENTIFICATION , 2006 .

[5]  G. Mercère,et al.  A New Recursive Method for Subspace Identification of Noisy Systems: EIVPM , 2003 .

[6]  Stéphane Lecoeuche,et al.  Propagator-based methods for recursive subspace model identification , 2008, Signal Process..

[7]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[8]  Si-Zhao Joe Qin,et al.  An overview of subspace identification , 2006, Comput. Chem. Eng..

[9]  Michel Verhaegen,et al.  Fast-array Recursive Closed-loop Subspace Model Identification , 2009 .

[10]  Bart De Moor,et al.  Algorithms for deterministic balanced subspace identification , 2005, Autom..

[11]  U. Kruger,et al.  Dynamic Principal Component Analysis Using Subspace Model Identification , 2005, ICIC.

[12]  Zhihuan Song,et al.  Recursive Subspace Model Identification Based on Vector Autoregressive Modelling , 2008 .

[13]  Lennart Ljung,et al.  A novel subspace identification approach with enforced causal models , 2005, Autom..

[14]  Tony Gustafsson,et al.  Instrumental variable subspace tracking using projection approximation , 1998, IEEE Trans. Signal Process..