| 城轨列车精确停车智能控制算法研究与仿真 |
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| 引用本文： | 孟建军,刘震.城轨列车精确停车智能控制算法研究与仿真[J].计算机工程与应用,2019,55(23):257-264. |
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| 作者姓名： | 孟建军 刘震 |
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| 作者单位： | 兰州交通大学 机电技术研究所,兰州 730070;甘肃省物流及运输装备信息化工程技术研究中心,兰州 730070;兰州交通大学 机电工程学院,兰州 730070;甘肃省物流及运输装备信息化工程技术研究中心,兰州 730070 |
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| 摘 要： | 随着我国城轨交通的大力发展，列车自动驾驶（ATO）系统在城轨列车中的应用越来越广泛，精确停车是衡量城轨列车自动驾驶性能重要指标之一。以精确停车、舒适性及能耗为指标，利用列车牵引计算知识建立列车运行多目标模型；利用遗传算法对该模型进行优化，结合MATLAB仿真软件得出列车运行理想目标曲线；运用SIMULINK模块分别搭建基于PID控制的仿真模型、基于模糊PID控制的仿真模型以及基于预测模糊PID控制的仿真模型，得出相应的列车运行跟踪曲线，并进行比较。结果表明：较前两者，预测模糊PID控制能最大程度地提高列车的停车精度。
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| 关 键 词： | 精确停车 遗传算法 模糊PID 预测模糊PID |
Research on Intelligent Algorithm for Precise Parking of Urban Rail Transit Based on Predictive Fuzzy PID |
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| MENG Jianjun,LIU Zhen.Research on Intelligent Algorithm for Precise Parking of Urban Rail Transit Based on Predictive Fuzzy PID[J].Computer Engineering and Applications,2019,55(23):257-264. |
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| Authors: | MENG Jianjun LIU Zhen |
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| Affiliation: | 1.Mechatronics T&R Institute, Lanzhou Jiaotong University, Lanzhou 730070, China
2.School of Mechatronic Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
3.Engineering Technology Center for Informatization of Logistics & Transport Equipment, Lanzhou 730070, China |
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| Abstract: | With the great development of urban rail transit in China, the Automatic Train Operation（ATO） system is more and more widely used in urban rail transit, precise parking is one of the important indexes to measure the autopilot performance of urban rail trains. In this paper， the multi-objective model of train operation is established by using the knowledge of train traction calculation with precise parking, comfort and energy consumption. Then, the model is optimized by genetic algorithm, and the ideal target curve of train running is obtained by MATLAB simulation software. Finally, the simulation model based on PID control, the simulation model based on fuzzy PID control and the simulation model based on predictive fuzzy PID control are built by using SIMULINK module, and the corresponding tracing curves of train operation are obtained and compared. The results show that, compared with the former two, the predictive fuzzy PID control can improve the parking precision of the train to the greatest extent. |
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| Keywords: | precision parking genetic algorithm fuzzy PID predictive fuzzy PID |
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