Reference:
Z. Su,
A. Núñez,
A. Jamshidi,
S. Baldi,
Z. Li,
R. Dollevoet, and
B. De Schutter,
"Model predictive control for maintenance operations planning of
railway infrastructures," in Computational Logistics
(Proceedings of the 6th International Conference on Computational
Logistics (ICCL'15), Delft, The Netherlands, Sept. 2015) (F. Corman,
S. Voß, and R.R. Negenborn, eds.), Lecture Notes in Computer
Science, Cham, Switzerland: Springer, ISBN 978-3-319-24263-7, pp.
673-688, 2015.
Abstract:
This paper develops a new decision making method for optimal planning
of railway maintenance operations using hybrid Model Predictive
Control (MPC). A linear dynamic model is used to describe the
evolution of the health condition of a segment of the railway track.
The hybrid characteristics arise from the three possible control
actions: performing no maintenance, performing corrective maintenance,
or doing a replacement. A detailed procedure for transforming the
linear system with switched input, and recasting the transformed
problem into a standard mixed integer quadratic programming problem is
presented. The merits of the proposed MPC approach for designing
railway track maintenance plans are demonstrated using a case study
with numerical simulations. The results highlight the potential of MPC
to improve condition-based maintenance procedures for railway
infrastructure.
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