Reference
B. De Schutter and
T. J. J. van den
Boom, "Model predictive control for discrete-event and hybrid systems," Tech.
report 03-012, Delft Center for Systems and Control, Delft University of
Technology, Delft, The Netherlands, 16 pp., Aug. 2003. Paper for the
Workshop on Nonlinear Predictive Control (Workshop S-5) at
the 42nd IEEE Conference on Decision and Control, Maui, Hawaii, Dec. 2003.
Abstract
Model predictive control (MPC) is a very popular controller design method in
the process industry. A key advantage of MPC is that it can accommodate
constraints on the inputs and outputs. Usually MPC uses linear or nonlinear
discrete-time models. In this paper we give an overview of some results in
connection with model predictive control (MPC) approaches for some tractable
classes of discrete-event systems and hybrid systems. In general the resulting
optimization problems are nonlinear and nonconvex. However, for some classes
tractable solution methods exist. In particular, we discuss MPC for
max-plus-linear systems, for mixed logical dynamical systems, and for
continuous piecewise-affine systems.
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BibTeX
@techreport{DeSvan:03-012,
author = {De Schutter, Bart and van den Boom, Ton J. J.},
title = {Model Predictive Control for Discrete-Event and Hybrid
Systems},
number = {03-012},
institution = {Delft Center for Systems and Control, Delft University of
Technology},
address = {Delft, The Netherlands},
month = aug,
year = {2003},
note = {Paper for the \emph{Workshop on Nonlinear Predictive Control
(Workshop S-5)} at the 42nd IEEE Conference on Decision and
Control, Maui, Hawaii, Dec.\ 2003}
}