A Model Predictive Control Approach for Recovery from Delays in
Railway Systems
Reference
B. De Schutter,
T. van den Boom, and
A. Hegyi,
"A Model Predictive Control Approach for Recovery from Delays in
Railway Systems," Proceedings of the 81st Annual
Meeting of the Transportation Research Board, Washington, DC,
13 pp., Jan. 2002. Paper 02-2707.
Abstract
We extend the model predictive control (MPC) framework, which is a
very popular controller design method in the process industry, to
transfer coordination in railway systems. In fact, the proposed
approach can also be used for other systems with both hard and soft
synchronization constraints, such as logistic operations. The main aim
of the control is to recover from delays in an optimal way by breaking
connections (at a cost). In general, the MPC control design problem
for railway systems leads to a nonlinear non-convex optimization
problem. We show that the optimal MPC strategy can also be computed
using an extended linear complementarity problem. Furthermore, we
present an extension with an extra degree of freedom to recover from
delays by letting some trains run faster than usual (again at a cost).
The resulting extended MPC railway problem can also be solved using an
extended linear complementarity problem.
Downloads
- Corresponding technical report:
pdf
file
(322 KB)
Bibtex entry
@inproceedings{DeSvan:01-08,
author={B. {D}e Schutter and T. van den Boom and A. Hegyi},
title={A Model Predictive Control Approach for Recovery from Delays in Railway
Systems},
booktitle={Proceedings of the 81st Annual Meeting of the Transportation Research
Board},
address={Washington, DC},
month=jan,
year={2002},
note={Paper 02-2707}
}
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Last update: February 21, 2026.