Brief paper: Convergence analysis of instrumental variable recursive subspace identification algorithms

Authors:
Guillaume Mercère;Marco Lovera
Affiliations:
Laboratoire d'Automatique et d'Informatique Industrielle, Université de Poitiers, 40 avenue du recteur Pineau, 86022 Poitiers, France;Dipartimento di Elettronica e Informazione, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
Venue:
Automatica (Journal of IFAC)
Year:
2007

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Abstract

The convergence properties of recently developed recursive subspace identification methods are investigated in this paper. The algorithms operate on the basis of instrumental variable (IV) versions of the propagator method for signal subspace estimation. It is proved that, under suitable conditions on the input signal and the system, the considered recursive subspace identification algorithms converge to a consistent estimate of the propagator and, by extension, to the state-space system matrices.