eprintid: 2458
rev_number: 7
eprint_status: archive
userid: 6
dir: disk0/00/00/24/58
datestamp: 2015-01-12 12:06:11
lastmod: 2015-01-12 12:06:11
status_changed: 2015-01-12 12:06:11
type: book_section
metadata_visibility: show
creators_name: Cerone, Vito
creators_name: Piga, Dario
creators_name: Regruto, Diego
creators_id: 
creators_id: dario.piga@imtlucca.it
creators_id: 
title: SM identification of input-output LPV models with uncertain time-varying parameters
ispublished: pub
subjects: QA75
divisions: CSA
full_text_status: none
abstract: In this chapter, we consider the identification of single-input single-output linear-parameter-varying models when both the output and the time-varying parameter measurements are affected by bounded noise. First, the  problem of computing exact parameter uncertainty intervals is formulated in terms of semialgebraic optimization. Then, a suitable relaxation tecnique is presented to compute parameter  bounds by means of convex optimization. Advantages of the presented approach with respect to previously published results are discussed.
date: 2012
series: Advanced Series in Electrical and Computer Engineering
number: 14
publisher: World Scientific
pagerange: 41-64
pages: 400
refereed: TRUE
isbn: 978-981-4355-44-5 
book_title: Linear parameter-varying system identification: new developments and trends
related_url_url: http://www.worldscientific.com/worldscibooks/10.1142/8186
related_url_type: pub
citation:   Cerone, Vito and Piga, Dario and Regruto, Diego  SM identification of input-output LPV models with uncertain time-varying parameters.   In:  Linear parameter-varying system identification: new developments and trends.   Advanced Series in Electrical and Computer Engineering  (14).  World Scientific, pp. 41-64.  ISBN 978-981-4355-44-5       (2012)