In this paper, we investigate the optimal control problem of heavy haul train on steep downward slope. Aiming to reduce train's maintenance cost and, most importantly, to ensure operation safety, a multi-stage dynamic programming model is formulated with the minimized in-train forces criteria. To solve the proposed model, this paper introduces a Q-learning algorithm considering operational requirements and the characteristics of air braking. As the size of a standard lookup table increases exponentially, we improve the computational performance and solution quality by maintaining a bounded lookup table. The computational results demonstrate the effectiveness and performance of the proposed model and algorithm.
Optimal control of heavy haul train on steep downward slope
2016-11-01
200528 byte
Conference paper
Electronic Resource
English
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