基于灰色遗传的高速列车速度控制器模型研究

Research on Speed Controller Model for High-speed Train Based on Grey Genetic Algorithm

速度控制器是列车自动驾驶系统(ATO)的核心,针对目前尚无研发成熟的速度控制器应用于高速列车的情况,引入灰色系统理论研究高速列车速度控制器模型;在灰色遗传预测模块中,对影响模型精度的λ值提出了基于遗传算法的求解方法,根据列车运行的4个目标设计其适应度函数,并加入先验知识判定对约束条件进行处理,同时建立新陈代谢GM(1,1)模型,在列车运行过程中不断求解新的模型参数a和b,实现模型在线校正,使系统可以进行长期预测;在灰色决策模块中,将高速列车的工况及运行目标转化为决策要素,应用灰靶决策产生最优策略控制列车运行;仿真结果显示了该模型应用于列车自动控速时的有效性和实时性,并使各项运行指标都有所提高。

The speed controller is the core of the automatic train operation （ATO） system. Gray System Theory that designs the high-- speed train speed controller model was introduced according to the current circumstance that there is no mature speed controller used in high speed train. In the grey genetic algorithm prediction module, genetic algorithm was proposed to solve ）, value which will impact the accura cy of the model. The fitness function was designed according to the four objectives of trains operation, and a priori knowledge of the determi nation was added to handle the constraint conditions. The new model parameter a and b were solved by the metabolic GM （ 1, 1） model dur ing trains operating constantly, which achieve model correction on--line and make the system longterm predict. In the gray decision-mak ing model, high--speed train conditions and objectives were transformed into the decision--making elements, and the gray target decision was introduced to make the optimal policy. Simulation verify the effectiveness and real--time performances of the proposed model, and the opera lion indicators were improved.