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Multi-mode and distributed model predictive control for whole day train regulation

机译:全日制火车的多模式和分布式模型预测控制

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To further improve the operation efficiency of metro trains, a multi-mode and distributed model predictive control (DMPC) algorithm is proposed for whole day train regulation of metro transportation in presence of time-varying passenger arrival rate and disturbances. Firstly, a multi-mode switching train operation model in a metro line is built with a switched linear function describing dynamic passenger demand. Secondly, a DMPC-based strategy for train regulation is proposed to ensure the punctuality and security of whole day train operation. Furthermore, numerical examples are present and the progress and practicability of the proposed train regulation strategy are illustrated, revealing that the proposed algorithm can significantly reduce the computation time so as to improve the real-time regulation performance.
机译:为了进一步提高地铁列车的运行效率,提出了一种多模式,分布式模型预测控制(DMPC)算法,用于在旅客到达率和时变因素存在干扰的情况下,对地铁的全天列车进行调节。首先,建立了具有描述动态乘客需求的线性转换函数的地铁线路多模式转换列车运行模型。其次,提出了一种基于DMPC的列车监管策略,以确保全天列车运行的准时性和安全性。此外,通过数值算例,说明了所提出的列车调节策略的进展和实用性,表明所提出的算法可以显着减少计算时间,从而提高实时调节性能。

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