Reference
T. J. J. van den Boom, B.
Heidergott, and B. De Schutter, "Complexity reduction in MPC for stochastic
max-plus-linear discrete event systems by variability expansion: Extended
report," Tech. report CSE02-016a, Control Systems Engineering, Fac. of
Information Technology and Systems, Delft University of Technology, Delft, The
Netherlands, 18 pp., Dec. 2006. A short version of this report has been
published in
Automatica, vol. 43, no. 6, pp. 1058-1063,
June 2007.
Abstract
Model predictive control (MPC) is a popular controller design technique in the
process industry. Recently, MPC has been extended to a class of discrete event
systems that can be described by a model that is "linear" in the max-plus
algebra. In this context both the perturbations-free case and for the case with
noise and/or modeling errors in a bounded or stochastic setting have been
considered. In each of these cases an optimization problem has to be solved
on-line at each event step in order to determine the MPC input. This paper
considers a method to reduce the computational complexity of this optimization
problem, based on variability expansion. In particular, it is shown that the
computational load is reduced if one decreases the level of "randomness" in the
system.
Downloads
Original paper
- T. J. J. van den Boom, B. Heidergott, and B. De Schutter, "Complexity reduction in MPC for stochastic max-plus-linear discrete event systems by variability expansion," Automatica, vol. 43, no. 6, pp. 1058-1063, June 2007. (online paper, abstract, bibtex, tech. report (pdf))
BibTeX
@techreport{vanHei:02-016a,
author = {van den Boom, Ton J. J. and Heidergott, Bernd and De
Schutter, Bart},
title = {Complexity Reduction in {MPC} for Stochastic Max-Plus-Linear
Discrete Event Systems by Variability Expansion: {E}xtended
Report},
number = {CSE02-016a},
institution = {Control Systems Engineering, Fac.\ of Information Technology
and Systems, Delft University of Technology},
address = {Delft, The Netherlands},
month = dec,
year = {2006},
note = {A short version of this report has been published in
\emph{Automatica}, vol.\ 43, no.\ 6, pp.\ 1058--1063, June
2007}
}