New approach to the estimation of the input matrices in subspace identification algorithms

In this paper we provide a different way to estimate matrices B and D, in subspace identification algorithms. The starting point was the method proposed by Van Overschee and De Moor (1996) - the only one applying subspace ideas to the estimation of those matrices. We have derived new (and simpler) e...

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Hauptverfasser:	Delgado, C.J.M., dos Santos, P.L., de Carvalho, J.L.M.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Applied sciences Computer science control theory systems Control theory. Systems Data engineering Electric variables measurement Exact sciences and technology Least squares methods Modelling and identification Noise measurement Null space Observability Robustness State estimation Stochastic processes White noise
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Zusammenfassung:	In this paper we provide a different way to estimate matrices B and D, in subspace identification algorithms. The starting point was the method proposed by Van Overschee and De Moor (1996) - the only one applying subspace ideas to the estimation of those matrices. We have derived new (and simpler) expressions and we found that the method proposed by Van Overschee and De Moor (1996) can be rewritten as a weighted least squares problem, involving the future outputs and inputs.
ISSN:	0191-2216
DOI:	10.1109/CDC.2004.1430376