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Optimal control of heavy haul train on steep downward slope

机译:陡峭向下斜坡上重载火车的最佳控制

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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.
机译:在本文中,我们调查了陡峭的向下斜坡上重载列车的最佳控制问题。 旨在降低火车的维护成本,最重要的是,为了确保操作安全,配制多级动态规划模型,以最小化的列车力量标准配制。 为了解决所提出的模型,本文介绍了考虑操作要求和空气制动特性的Q学习算法。 随着标准查找表的大小指数增加,我们通过维护有界查找表来提高计算性能和解决方案质量。 计算结果证明了所提出的模型和算法的有效性和性能。

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