Model Predictive Control for Railway Networks
Reference
B. De Schutter and
T. van den Boom,
"Model Predictive Control for Railway Networks," Proceedings of the 2001 IEEE/ASME International Conference
on Advanced Intelligent Mechatronics (AIM'01), Como, Italy, pp.
105-110, July 2001.
Abstract
Model predictive control (MPC) is a very popular controller design
method in the process industry. Usually MPC uses linear discrete-time
models. In this paper we extend MPC to a class of discrete-event
systems with both hard and soft synchronization constraints. Typical
examples of such systems are railway networks, subway networks, and
other logistic operations. In general the MPC control design problem
for these systems leads to a nonlinear non-convex optimization
problem. We also show that the optimal MPC strategy can be computed
using an extended linear complementarity problem.
Downloads
- Corresponding technical report:
pdf
file
(333 KB)
Bibtex entry
@inproceedings{DeSvan:00-17,
author={B. {D}e Schutter and T. van den Boom},
title={Model Predictive Control for Railway Networks},
booktitle={Proceedings of the 2001 IEEE/ASME International Conference on
Advanced Intelligent Mechatronics (AIM'01)},
address={Como, Italy},
pages={105--110},
month=jul,
year={2001}
}
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Last update: February 21, 2026.