eprintid: 1022
rev_number: 10
eprint_status: archive
userid: 44
dir: disk0/00/00/10/22
datestamp: 2011-12-05 09:47:20
lastmod: 2013-03-12 14:57:38
status_changed: 2011-12-05 09:47:20
type: article
metadata_visibility: show
creators_name: Patrinos, Panagiotis
creators_name: Sarimveis, Haralambos
creators_name: Sopasakis, Pantelis
creators_id: panagiotis.patrinos@imtlucca.it
creators_id: 
creators_id: pantelis.sopasakis@imtlucca.it
title: A global piecewise smooth Newton method for fast large-scale model predictive control
ispublished: pub
subjects: QA75
subjects: TJ
divisions: CSA
full_text_status: none
keywords: Model predictive control; Online optimization; Large-scale systems
abstract: In this paper, the strictly convex quadratic program (QP) arising in model predictive control (MPC) for constrained linear systems is reformulated as a system of piecewise affine equations. A regularized piecewise smooth Newton method with exact line search on a convex, differentiable, piecewise-quadratic merit function is proposed for the solution of the reformulated problem. The algorithm has considerable merits when applied to MPC over standard active set or interior point algorithms. Its performance is tested and compared against state-of-the-art QP solvers on a series of benchmark problems. The proposed algorithm is orders of magnitudes faster, especially for large-scale problems and long horizons. For example, for the challenging crude distillation unit model of Pannocchia, Rawlings, and Wright (2007) with 252 states, 32 inputs, and 90 outputs, the average running time of the proposed approach is 1.57 ms.
date: 2011-09
date_type: published
publication: Automatica
volume: 47
number: 9
publisher: Elsevier 
pagerange: 2016-2022
id_number: 10.1016/j.automatica.2011.05.024
refereed: TRUE
issn: 0005-1098
official_url: http://www.sciencedirect.com/science/article/pii/S0005109811002974
citation:   Patrinos, Panagiotis and Sarimveis, Haralambos and Sopasakis, Pantelis  A global piecewise smooth Newton method for fast large-scale model predictive control.  Automatica, 47 (9).  pp. 2016-2022.  ISSN 0005-1098      (2011)