Treffer: Convergence analysis of instrumental variable recursive subspace identification algorithms

Title:
Convergence analysis of instrumental variable recursive subspace identification algorithms
Authors:
Mercère, Guillaume, Lovera, Marco
Contributors:
Laboratoire d'automatique et d'informatique industrielle EA 1219 (LAII Poitiers ), Université de Poitiers = University of Poitiers (UP), Dipartimento di Elettronica e Informazione, Politecnico di Milano Milan (POLIMI)
Source:
14th IFAC Symposium on System Identification, SYSID'2006
https://hal.science/hal-00098152
14th IFAC Symposium on System Identification, SYSID'2006, Mar 2006, Newcastle, Australia. pp.CDROM
Publisher Information:
CCSD
Publication Year:
2006
Collection:
Université de Poitiers: Publications de nos chercheurs.ses (HAL)
Subject Terms:
Subspace methods, Recursive algorithms, Identification algorithms, State space models, Tracking systems, Convergence analysis, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Subject Geographic:
Newcastle, Australia
Document Type:
Konferenz conference object
Language:
English
Availability:
https://hal.science/hal-00098152
https://hal.science/hal-00098152v1/document
https://hal.science/hal-00098152v1/file/ML_SYSID06.pdf
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edsbas.3FDC48FE
Database:
BASE

Weitere Informationen

International audience ; The convergence properties of a recently developed recursive subspace identification algorithm of the MOESP class are investigated in this paper. The algorithm operates on the basis of an extended instrumental variable (EIV) version of the propagator method for signal subspace estimation. It is proved that, under weak conditions on the input signal and the identified system, the considered recursive subspace identification algorithm converges to a consistent estimate of the propagator and, by extension, of the state space system matrices