System identification in the presence of unmodeled dynamics-aprincipal components extraction approach
Yanghai Tsin
Yaotong Li
Inst. of Autom., Acad. Sinica, Beijing;
This paper appears in: Decision and Control, 1996., Proceedings of the 35th IEEE
Publication Date: 11-13 Dec 1996
Volume: 3,
On page(s): 2555-2556 vol.3
Meeting Date: 12/11/1996 - 12/13/1996
Location: Kobe, Japan
ISBN: 0-7803-3590-2
References Cited: 3
INSPEC Accession Number: 5540151
Digital Object Identifier: 10.1109/CDC.1996.573483
Current Version Published: 2002-08-06
Abstract
In this paper a two-step method for identification is presented.
The first step is to identify FIR sequences using any existing efficient
algorithm. The second step is principal components extraction. It tries
to recover the complete system performance from the FIR sequences
estimated. It is shown that the denominator parameter of the obtained
ARMAX model is the eigenvector corresponding to the eigenvalue of a
certain matrix composed of the estimated FIR sequence. The eigenvalue
itself can be an index of model order selection. A criterion for
selecting the FIR sequence length is presented. Simulation result
demonstrates the effectiveness of the approach
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