DocumentCode
2021265
Title
α-optimality evaluation in H∞ identification of low-order uncertainty models
Author
Giarre, L. ; Malan, S. ; Milanese, M.
Author_Institution
Dipt. di Autom. e Inf., Politecnico di Torino, Italy
Volume
1
fYear
1997
fDate
10-12 Dec 1997
Firstpage
175
Abstract
Set membership (SM) H∞ identification is investigated, aimed to estimate a low order approximate model and its identification error, without requiring the selection of a-priori basis for the model class. An α-optimal algorithm is determined using time domain data and assuming l∞ bounded measurement errors and exponentially stable systems. The algorithm presented is proven to be strongly convergent
Keywords
Banach spaces; H∞ optimisation; discrete time systems; error analysis; identification; linear systems; time-domain analysis; uncertain systems; Banach space; H∞ identification; discrete time systems; exponentially stable systems; linear systems; low-order uncertainty models; measurement errors; optimisation; set membership; time domain data; Control design; Ear; Finite impulse response filter; Frequency selective surfaces; Q measurement; Transfer functions; Upper bound;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location
San Diego, CA
ISSN
0191-2216
Print_ISBN
0-7803-4187-2
Type
conf
DOI
10.1109/CDC.1997.650610
Filename
650610
Link To Document