A new insight to the matrices extraction in a MOESP type subspace identification algorithm

• Type: Article in International Scientific Journal
• Date: 2006

Authors

Catarina Delgado (Author) FEP; P. Lopes dos Santos (Author) FEUP; Martins De Carvalho, JLM (Author) Other

Journal

Title: International Journal of Systems Science

Vol. 37 No. 8

Pages: 565-574

ISSN: 0020-7721

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 2 Citations

Scopus - 2 Citations

Scientific classification

FOS: Engineering and technology > Other engineering and technologies

CORDIS: Technological sciences > Engineering > Electrical engineering

Other information

Authenticus ID: P-004-K4Q

DOI: 10.1080/00207720600784486

Abstract (EN): In this paper we analyse the estimates of the matrices produced by the non-biased deterministic-stochastic subspace identification algorithms (NBDSSI) proposed by Van Overschee and De Moor ( 1996). First, an alternate expression is derived for the A and C estimates. It is shown that the Chiuso and Picci result ( Chiuso and Picci 2004) stating that the A and C estimates delivered by this algorithm robust version and by the Verhaegen's MOESP (Verhaegen and Dewilde 1992a, Verhaegen and Dewilde 1992b, Verhaegen 1993, Verhaegen 1994) are equal, can be obtained from this expression. An alternative approach for the estimation of matrices B and D in subspace identification is also described. It is shown that the least squares approach for the estimation of these matrices estimation can be just expressed as an orthogonal projection of the future outputs on a lower dimension subspace in the orthogonal complement of the column space of the extended observability matrix. Since this subspace has a dimension equal to the number of outputs, a simpler and numerically more efficient ( but equally accurate) new subspace algorithm is provided.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10