DocumentCode :
3441136
Title :
Informative data and identifiability in LPV-ARX prediction-error identification
Author :
Dankers, Arne G. ; Tóth, Roland ; Heuberger, Peter S C ; Bombois, Xavier ; Van den Hof, Paul M J
Author_Institution :
Delft Center for Syst. & Control, Delft Univ. of Technol., Delft, Netherlands
fYear :
2011
fDate :
12-15 Dec. 2011
Firstpage :
799
Lastpage :
804
Abstract :
In system identification, the concepts of informative data and identifiable model structures are important for addressing the statistical properties of estimated models. In this paper, these two concepts are generalized from the classical LTI prediction-error identification framework to the situation of LPV model structures and appropriate definitions are introduced. For two particular cases (piecewise constant and periodic scheduling trajectories) conditions are derived for the data sets to be informative w.r.t. the LPV-ARX model structure. Moreover, conditions are derived under which the LPV-ARX model structure is globally identifiable.
Keywords :
linear systems; parameter estimation; piecewise constant techniques; predictive control; variable structure systems; LPV-ARX prediction-error identification; classical LTI prediction-error identification framework; identifiable model structure; informative data; linear parameter-varying framework; periodic scheduling trajectories; piecewise constant trajectories; system identification; Bismuth; Data models; Delta modulation; Noise; Predictive models; Vectors; Zinc;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control and European Control Conference (CDC-ECC), 2011 50th IEEE Conference on
Conference_Location :
Orlando, FL
ISSN :
0743-1546
Print_ISBN :
978-1-61284-800-6
Electronic_ISBN :
0743-1546
Type :
conf
DOI :
10.1109/CDC.2011.6161201
Filename :
6161201
Link To Document :
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