eprintid: 1841
rev_number: 13
eprint_status: archive
userid: 44
dir: disk0/00/00/18/41
datestamp: 2013-10-25 08:30:43
lastmod: 2014-06-16 10:17:42
status_changed: 2013-10-25 08:30:43
type: article
metadata_visibility: show
creators_name: Sopasakis, Pantelis
creators_name: Patrinos, Panagiotis
creators_name: Sarimveis, Haralambos
creators_id: pantelis.sopasakis@imtlucca.it
creators_id: panagiotis.patrinos@imtlucca.it
creators_id: 
title: MPC for Sampled-Data Linear Systems: guaranteeing continuous-time positive invariance
ispublished: pub
subjects: QA
subjects: QA75
subjects: TA
subjects: TK
divisions: CSA
full_text_status: none
keywords: Continuous invariance; model predictive control; polytopic overapproximation; sampled data

abstract: Model Predictive Controllers (MPC) designed for sampled-data systems can be shown to violate the constraints in continuous time. A reformulation of the initial problem will guarantee constraint satisfaction throughout the intersample period. Polytopic inclusions of the continuous trajectory are used in this paper to establish additional constraints leading to a linearly constrained quadratic optimization problem. Continuous time asymptotic stability and continuous-time positive invariance are proven for the reformulated problem.
date: 2014-04
date_type: published
publication: IEEE Transactions on Automatic Control 
volume: 59
number: 4
publisher: IEEE 
pagerange: 1088-1093
id_number: 10.1109/TAC.2013.2285786
refereed: TRUE
issn: 0018-9286
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6632877&isnumber=6776438
citation:   Sopasakis, Pantelis and Patrinos, Panagiotis and Sarimveis, Haralambos  MPC for Sampled-Data Linear Systems: guaranteeing continuous-time positive invariance.  IEEE Transactions on Automatic Control , 59 (4).  pp. 1088-1093.  ISSN 0018-9286      (2014)