Reference
B. De Schutter and
T. J. J. van den
Boom, "Model predictive control for max-min-plus-scaling systems,"
Proceedings of the 2001 American Control Conference,
Arlington, Virginia, pp. 319-324, June 2001.
Abstract
We further extend the model predictive control framework, which is very popular
in the process industry due to its ability to handle constraints on inputs and
outputs, to a class of discrete event systems that can be modeled using the
operations maximization, minimization, addition and scalar multiplication. This
class encompasses max-plus-linear systems, min-max-plus systems, bilinear
max-plus systems and polynomial max-plus systems. In general the model
predictive control problem for max-min-plus-scaling systems leads to a
nonlinear non-convex optimization problem, that can also be reformulated as an
optimization problem over the solution set of an extended linear
complementarity problem. We also show that under certain conditions the
optimization problem reduces to a convex programming problem, which can be
solved very efficiently.
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BibTeX
@inproceedings{DeSvan:00-03,
author = {De Schutter, Bart and van den Boom, Ton J. J.},
title = {Model Predictive Control for Max-Min-Plus-Scaling Systems},
booktitle = {Proceedings of the 2001 American Control Conference},
address = {Arlington, Virginia},
pages = {319--324},
month = jun,
year = {2001}
}