Model Predictive Control for Randomly Switching Max-Plus-Linear
Systems Using a Scenario-Based Algorithm
Reference
T. van den Boom and
B. De Schutter,
"Model Predictive Control for Randomly Switching Max-Plus-Linear
Systems Using a Scenario-Based Algorithm," Proceedings of the 49th IEEE Conference on Decision and
Control, Atlanta, Georgia, pp. 2298-2303, Dec. 2010.
Abstract
Switching max-plus-linear (SMPL) systems are discrete event systems
that can switch between different modes of operation. In each mode the
system is described by a max-plus-linear state equation and a
max-plus-linear output equation, with different system matrices for
each mode. The switching between from one mode to the other is a
stochastic process. In the model predictive control (MPC) formulation
stability is enforced by additional constraints. To reduce the
computational complexity we use an algorithm based on scenario
generation for such stochastic SMPL systems.
Downloads
- Corresponding technical report:
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Bibtex entry
@inproceedings{vanDeS:10-050,
author={T. van den Boom and B. {D}e Schutter},
title={Model Predictive Control for Randomly Switching Max-Plus-Linear Systems
Using a Scenario-Based Algorithm},
booktitle={Proceedings of the 49th IEEE Conference on Decision and Control},
address={Atlanta, Georgia},
pages={2298--2303},
month=dec,
year={2010}
}
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Last update: February 21, 2026.