Reference
B. De Schutter and T. van den Boom, "Model predictive control for
max-plus-linear discrete-event systems: Extended report & addendum," Tech.
report bds:99-10a, Control Systems Engineering, Fac. of Information Technology
and Systems, Delft University of Technology, Delft, The Netherlands, 27 pp.,
Nov. 2000. A short version of this report has been published in
Automatica, vol. 37, no. 7, pp. 1049-1056, July 2001.
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 discrete-time
models. In this report we extend MPC to a class of discrete-event systems that
can be described by models that are "linear" in the max-plus algebra, which has
maximization and addition as basic operations. In general the resulting
optimization problem are nonlinear and non-convex. However, if the control
objective and the constraints depend monotonically on the outputs of the
system, the model predictive control problem can be recast as problem with a
convex feasible set. If in addition the objective function is convex, this
leads to a convex optimization problem, which can be solved very efficiently.
Downloads
Original paper
BibTeX
@techreport{DeSvan:99-10a,
author = {De Schutter, Bart and van den Boom, Ton},
title = {Model Predictive Control for Max-Plus-Linear Discrete-Event
Systems: {E}xtended Report \& Addendum},
number = {bds:99-10a},
institution = {Control Systems Engineering, Fac.\ of Information Technology
and Systems, Delft University of Technology},
address = {Delft, The Netherlands},
month = nov,
year = {2000},
note = {A short version of this report has been published in
\emph{Automatica}, vol.\ 37, no.\ 7, pp.\ 1049--1056, July
2001}
}