Reference
B. De Schutter and T. van den Boom, "Model predictive control for max-min-plus
systems," in
Discrete Event Systems: Analysis and Control
(Proceedings of the 5th International Workshop on Discrete Event Systems
(WODES2000), Ghent, Belgium, Aug. 2000) (R. Boel and G. Stremersch, eds.), vol.
569 of
The Kluwer International Series in Engineering and
Computer Science, Boston, Massachusetts: Kluwer Academic Publishers, pp.
201-208, 2000.
Abstract
Model predictive control (MPC) is a widely used control design method in the
process industry. Its main advantage is that it allows the inclusion of
constraints on the inputs and outputs. Usually MPC uses linear discrete-time
models. We extend MPC to max-min-plus discrete event systems. In general the
resulting optimization problems are nonlinear and nonconvex. However, if the
state equations are decoupled and if the control objective and the constraints
depend monotonically on the states and outputs of system, the
max-min-plus-algebraic MPC 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
BibTeX
@incollection{DeSvan:00-01,
author = {De Schutter, Bart and van den Boom, Ton},
title = {Model Predictive Control for Max-Min-Plus Systems},
booktitle = {Discrete Event Systems: Analysis and Control
\normalfont(Proceedings of the 5th International Workshop on
Discrete Event Systems (WODES2000), Ghent, Belgium, Aug.
2000)},
series = {The Kluwer International Series in Engineering and Computer
Science},
volume = {569},
editor = {Boel, Ren\'{e} and Stremersch, Geert},
publisher = {Kluwer Academic Publishers},
address = {Boston, Massachusetts},
pages = {201--208},
year = {2000}
}