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.
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BibTeX
@inproceedings{Kervan:15-016,
author = {Kersbergen, Bart and van den Boom, Ton and De Schutter, Bart},
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}
}