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Recursive Subspace Identification Based on Principal Component Analysis

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2 Author(s)
Yue-Ping Jiang ; Acad. of Math. & Syst. Sci., Chinese Acad. of Sci., Beijing, China ; Hai-tao Fang

The problem of recursive subspace identification of state-space models is considered in this paper. A new recursive algorithm based on SA-PCA (stochastic approximation-principal component analysis) is proposed to estimate a basis of the extended observability matrix in the noise-free case. Besides, a recursive algorithm based on RLS (Recursive Least-Squares) is proposed to estimate the system matrices. The algorithm is evaluated by a simulation study.

Published in:

Control Conference, 2006. CCC 2006. Chinese

Date of Conference:

7-11 Aug. 2006