Reference
T. J. J. van den Boom and B. De
Schutter, "Model predictive control for perturbed max-plus-linear systems,"
Systems & Control Letters, vol. 45, no. 1, pp.
21-33, Jan. 2002.
Abstract
Model predictive control (MPC) is a popular controller design technique in the
process industry. Conventional MPC uses linear or nonlinear discrete-time
models. Recently, we have extended MPC to a class of discrete event systems
that can be described by a model that is "linear" in the (max,+) algebra. In
our previous work we have only considered MPC for the deterministic noise-free
case without modeling errors. In this paper we extend our previous results on
MPC for max-plus-linear systems to cases with noise and/or modeling errors. We
show that under quite general conditions the resulting optimization problems
can be solved very efficiently.
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BibTeX
@article{vanDeS:00-18,
author = {van den Boom, Ton J. J. and De Schutter, Bart},
title = {Model Predictive Control for Perturbed Max-Plus-Linear Systems},
journal = {Systems \& Control Letters},
volume = {45},
number = {1},
pages = {21--33},
month = jan,
year = {2002}
}