Convergence analysis of instrumental variable recursive subspace identification algorithms

Guillaume Mercère (1) , Marco Lovera (2)

1 LAII [Poitiers] - Laboratoire d'automatique et d'informatique industrielle [EA 1219]
2 Dipartimento di Elettronica e Informazione

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.

Mots clés: Subspace methods; recursive algorithms; linear systems; instrumental variable; convergence analysis

Domaines: Automatique / Robotique

Guillaume Mercère, Marco Lovera. Convergence analysis of instrumental variable recursive subspace identification algorithms. Automatica, 2007, 43, pp.1377-1386. ⟨10.1016/j.automatica.2007.01.014⟩. ⟨hal-00169461v2⟩