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针对列车制动过程存在的复杂性、非线性、时变性、不确定性等因素,通过分析影响建立BP神经网络模型的主要因素,建立了用于列车制动控制的BP神经网络模型。以货物列车为仿真对象,在Matlab环境中进行了仿真研究。仿真结果表明,该方法控制安全性好、停车误差小,基于BP神经网络的智能算法运用于列车制动控制是可行的。
Aiming at the complexity, non-linearity, time-varying and uncertainty of train braking process, a BP neural network model for train braking control is established by analyzing the main factors that affect the establishment of BP neural network model. Taking the freight train as the simulation object, the simulation research is carried out in Matlab environment. Simulation results show that this method has good control safety and small parking error. It is feasible to apply intelligent algorithm based on BP neural network to train brake control.