**Reference:**

B. Kersbergen,
T. van den Boom, and
B. De Schutter,
"Improved distributed model predictive control for rescheduling of
railway traffic by manipulation of the cost functions,"
*Proceedings of the 6th International Conference on Railway
Operations Modelling and Analysis (RailTokyo2015)*, Narashino,
Japan, 13 pp., Mar. 2015. Paper 025.

**Abstract:**

In this paper we introduce two distributed model predictive control
(DMPC) approaches that significantly improve the quality of the
solutions found compared to the DMPC approaches that were introduced
by Kerbergen et al. in the paper "Distributed model predictive
control for rescheduling of railway traffic" (by B. Kersbergen, T.J.J.
van den Boom, and B. De Schutter, *Proceedings of the 17th
International IEEE Conference on Intelligent Transportation Systems
(ITSC2014)*, Qingdao, China, pp. 2732–2737, Oct. 2014). for the
rescheduling of railway traffic, while the computation time only
increased by a small fraction. In DMPC the global rescheduling problem
is split up into several local problems that are solved by local model
predictive controllers that communicate with each other to achieve a
solution for the global rescheduling problem. We improve the solution
found by the DMPC approaches by adjusting the weights in the local
problems such that the delay propagation through the network is
reduced. We compare the performance in terms of computation time and
delay reduction of the different DMPC approaches with the global model
predictive control approach for different lengths of the prediction
horizon.

Corresponding technical report: pdf file (460 KB)

@inproceedings{Kervan:15-016,

author={B. Kersbergen and T. van den Boom and B. {D}e Schutter},

title={Improved distributed model predictive control for rescheduling of railway traffic by manipulation of the cost functions},

booktitle={Proceedings of the 6th International Conference on Railway Operations Modelling and Analysis (RailTokyo2015)},

address={Narashino, Japan},

month=mar,

year={2015},

note={Paper 025}

}

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