eprintid: 1480
rev_number: 9
eprint_status: archive
userid: 44
dir: disk0/00/00/14/80
datestamp: 2013-02-14 10:04:07
lastmod: 2013-03-12 14:57:38
status_changed: 2013-02-14 10:04:07
type: book_section
metadata_visibility: show
creators_name: Sopasakis, Pantelis
creators_name: Patrinos, Panagiotis
creators_name: Sarimveis, Haralambos
creators_name: Bemporad, Alberto
creators_id: pantelis.sopasakis@imtlucca.it
creators_id: panagiotis.patrinos@imtlucca.it
creators_id: 
creators_id: alberto.bemporad@imtlucca.it
title: Model Predictive Control for Linear Impulsive Systems
ispublished: pub
subjects: QA75
subjects: TJ
divisions: CSA
full_text_status: none
keywords: Asymptotic stability; Drugs; Mathematical model; Optimal control; Stability analysis; Standards; Trajectory
abstract: Linear Impulsive Control Systems have been extensively studied with respect to their equilibrium points which, in most cases, are no other than the origin. However, the trajectory of the system cannot be stabilized to arbitrary desired points which imposes a significant restriction towards their utilization in various applications such as drug administration. In this paper, we study the equilibrium of Linear Impulsive Systems in light of target-sets instead of the standard equilibrium point approach. We properly extend the notion of invariant sets which is crucial in designing asymptotically stable Model Predictive Controllers (MPC).
date: 2012-12
date_type: published
publisher: IEEE
pagerange: 5164 -5169
event_title: Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
id_number: 10.1109/CDC.2012.6426243
refereed: TRUE
isbn: 978-1-4673-2064-1
book_title: Proceedings of the IEEE 51st Annual Conference on Decision and Control (CDC), 2012
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6426243&isnumber=6425800
citation:   Sopasakis, Pantelis and Patrinos, Panagiotis and Sarimveis, Haralambos and Bemporad, Alberto  Model Predictive Control for Linear Impulsive Systems.   In:  Proceedings of the IEEE 51st Annual Conference on Decision and Control (CDC), 2012.   IEEE, 5164 -5169.  ISBN 978-1-4673-2064-1      (2012)