eprintid: 1470
rev_number: 8
eprint_status: archive
userid: 6
dir: disk0/00/00/14/70
datestamp: 2013-02-12 12:03:40
lastmod: 2013-02-12 12:03:40
status_changed: 2013-02-12 12:03:40
type: book_section
metadata_visibility: show
creators_name: Patrinos, Panagiotis
creators_name: Bemporad, Alberto
creators_id: panagiotis.patrinos@imtlucca.it
creators_id: alberto.bemporad@imtlucca.it
title: An accelerated dual gradient-projection algorithm for linear model predictive control
ispublished: pub
subjects: QA75
subjects: TJ
divisions: CSA
full_text_status: none
keywords: Acceleration; Convergence; Optimization; Prediction  Algorithms; Predictive control; Tin; Vectors
note: 51st IEEE Conference on Decision and Control
December 10-13, 2012. Maui, Hawaii, USA
abstract: This paper proposes a dual fast gradient-projection method for solving quadratic programming problems that arise in linear model predictive control with general polyhedral constraints on inputs and states. The proposed algorithm is quite suitable for embedded control applications in that: (1) it is extremely simple and easy to code; (2) the number of iterations to reach a given accuracy in terms of optimality and feasibility of the primal solution can be estimated quite tightly; (3) the computational cost per iteration increases only linearly with the prediction horizon; and (4) the algorithm is also applicable to linear time-varying (LTV) model predictive control problems, with an extra on-line computational effort that is still linear with the prediction horizon.
date: 2012-12
date_type: published
publisher: IEEE
pagerange: 662 -667
event_title: Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
id_number: 10.1109/CDC.2012.6426458
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=6426458&isnumber=6425800
citation:   Patrinos, Panagiotis and Bemporad, Alberto  An accelerated dual gradient-projection algorithm for linear model predictive control.   In:  Proceedings of the IEEE 51st Annual Conference on Decision and Control (CDC), 2012.   IEEE, 662 -667.  ISBN 978-1-4673-2064-1      (2012)