eprintid: 544
rev_number: 9
eprint_status: archive
userid: 7
dir: disk0/00/00/05/44
datestamp: 2011-07-27 08:40:49
lastmod: 2011-08-04 07:29:07
status_changed: 2011-07-27 08:40:49
type: book_section
metadata_visibility: show
contact_email: alberto.bemporad@imtlucca.it
item_issues_count: 0
creators_name: Bemporad, Alberto
creators_id: alberto.bemporad@imtlucca.it
title: Model predictive control Design: New Trends and Tools 
ispublished: pub
subjects: QA75
subjects: TJ
divisions: CSA
full_text_status: none
keywords: dynamical model; feedback controllers; linear feedback gain; lookup table; model predictive control design; open-loop system; optimization problem; quadratic programming; control system synthesis; feedback; open loop systems; predictive control; quadratic programming; table lookup
abstract: Model-based design is well recognized in industry as a systematic approach to the development, evaluation, and implementation of feedback controllers. Model predictive control (MPC) is a particular branch of model-based design: a dynamical model of the open-loop process is explicitly used to construct an optimization problem aimed at achieving the prescribed system's performance under specified restrictions on input and output variables. The solution of the optimization problem provides the feedback control action, and can be either computed by embedding a numerical solver in the real-time control code, or pre-computed off-line and evaluated through a lookup table of linear feedback gains. This paper reviews the basic ideas of MPC design, from the traditional linear MPC setup based on quadratic programming to more a advanced explicit and hybrid MPC, and highlights available software tools for the design, evaluation, code generation, and deployment of MPC controllers in real-time hardware platforms
date: 2006
date_type: published
publication: Decision and Control
publisher: IEEE
place_of_pub: 13th-15th December 2006
pagerange: 6678-6683
event_title: 45th IEEE Conference on Decision and Control
event_location: 13th-15th December 2006
event_dates: San Diego
id_number: 10.1109/CDC.2006.377490
refereed: TRUE
isbn: 1-4244-0171-2
book_title: Decision and Control
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4178103&isnumber=4176993
citation:   Bemporad, Alberto  Model predictive control Design: New Trends and Tools.   In:  Decision and Control.   IEEE, 13th-15th December 2006, pp. 6678-6683.  ISBN 1-4244-0171-2      (2006)