eprintid: 577
rev_number: 10
eprint_status: archive
userid: 7
dir: disk0/00/00/05/77
datestamp: 2011-07-27 09:09:07
lastmod: 2014-07-17 12:47:14
status_changed: 2011-07-27 09:09:07
type: book_section
metadata_visibility: show
item_issues_count: 0
creators_name: Bemporad, Alberto
creators_name: Morari, Manfred
creators_id: alberto.bemporad@imtlucca.it
creators_id: 
title: Optimization-based hybrid control tools
ispublished: pub
subjects: QA
subjects: QA75
subjects: TJ
divisions: CSA
full_text_status: none
keywords: HYSDEL; MLD models; Mixed Logical Dynamical systems; Model Predictive Control; controller design; modeling language; multiparametric programming; piecewise linear control; control system CAD; linear systems; optimal control; piecewise linear techniques; predictive control; reachability analysis
abstract: The paper discusses a framework for modeling, analyzing and controlling systems whose behavior is governed by interdependent physical laws, logic rules, and operating constraints, denoted as Mixed Logical Dynamical (MLD) systems. They are described by linear dynamic equations subject to linear inequalities involving real and integer variables. MLD models are equivalent to various other system descriptions like Piecewise Affine (PWA) systems and Linear Complementarity (LC) systems. They have the advantage, however, that many problems of system analysis (like reachability/controllability, observability, and verification) and many problems of synthesis (like controller design and filter design) can be readily expressed as mixed integer linear or quadratic programs, for which many commercial software packages exist. In this paper we first recall MLD models and the modeling language HYSDEL (HYbrid Systems DEscription Language). Subsequently, we illustrate the use of Model Predictive Control (MPC) based on mixed-integer programming for hybrid MLD models, and the use of multiparametric programming for obtaining explicitly the equivalent piecewise linear control form of MPC. The eventual practical success of these methods will depend on progress in the development of the various optimization algorithms and tools so that problems of realistic size can be tackled
date: 2001
date_type: published
publication: American Control Conference
volume: 2
publisher: IEEE
place_of_pub: Arlington, VA June 25-27, 2001
pagerange: 1689 -1703 
event_dates: Arlington, VA
id_number: 10.1109/ACC.2001.945973
refereed: TRUE
isbn: 0-7803-6495-3 
book_title: American Control Conference
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=945973&isnumber=20470
citation:   Bemporad, Alberto and Morari, Manfred  Optimization-based hybrid control tools.   In:  American Control Conference.   IEEE, Arlington, VA June 25-27, 2001, 1689 -1703 .  ISBN 0-7803-6495-3       (2001)