Min-Max Model Predictive Control for Uncertain Max-Min-Plus-Scaling
Systems
Reference
I. Necoara,
B. De Schutter,
T. van den Boom, and
H. Hellendoorn,
"Min-Max Model Predictive Control for Uncertain Max-Min-Plus-Scaling
Systems," Proceedings of the 8th International
Workshop on Discrete Event Systems (WODES'06), Ann Arbor,
Michigan, pp. 439-444, July 2006.
Abstract
We extend the model predictive control (MPC) framework that has been
developed previously to a class of uncertain 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. We first consider open-loop
min-max MPC and we show that the resulting optimization problem can be
transformed into a set of linear programming problems. Then, min-max
feedback model predictive control using disturbance feedback policies
is presented, which leads to improved performance compared to the
open-loop approach.
Downloads
- Corresponding technical report:
pdf
file
(285 KB)
Bibtex entry
@inproceedings{vanDeS:06-011,
author={I. Necoara and B. {D}e Schutter and T. van den Boom and H.
Hellendoorn},
title={Min-Max Model Predictive Control for Uncertain Max-Min-Plus-Scaling
Systems},
booktitle={Proceedings of the 8th International Workshop on Discrete Event
Systems (WODES'06)},
address={Ann Arbor, Michigan},
pages={439--444},
month=jul,
year={2006}
}
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Last update: February 21, 2026.