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自动驾驶系统运行模式曲线最优预见跟踪控制算法 被引量:5

Optimal preview tracking control algorithm for ATO system
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摘要 为研究城轨列车自动驾驶系统(ATO)运行模式曲线跟踪算法,通过分析列车运行过程,结合列车牵引计算模型,建立不同工况下的动力学模型。在保障平稳驾驶和操纵合理性基础上,提出跟踪算法的设计目标,即在保障舒适性的前提下实现高精度的速度跟踪及精确停车。将列车运行控制系统与最优预见跟踪控制相结合,以自动驾驶系统离线优化计算的运行模式曲线为目标,线路附加阻力及基本阻力视为扰动,设计城轨列车自动驾驶系统运行模式曲线最优预见跟踪控制算法。为验证该算法的有效性,引入PID控制进行仿真对比。仿真结果表明,设计的算法在兼顾了运行舒适性的同时,具有良好的速度跟踪性并满足停车精度要求。 Aiming at studying Automatic Train Operation( ATO) systems, by analyzing the automatic operation process of urban trains and combining the train traction calculation model, the dynamic model in different operation modes for urban trains was built. On the basis of smooth driving and rational operation, the goals of an automatic train control method were proposed, to realize the precise speed tracking and train stop on premise of comfort. Then the automatic train control method based on optimal preview tracking control system was proposed. This method was designed on taking operation speed curve calculated by ATO as target and regarding additional resistance and basic resistance as disturbance. In order to verify the correctness of this control method, the PID control was introduced. The simulation results show this optimal preview tracking control method has a good performance on speed tracking and train stop with the satisfaction of comfort.
出处 《计算机应用》 CSCD 北大核心 2017年第A02期266-269,305,共5页 journal of Computer Applications
基金 中国铁路总公司科技研究开发计划项目(2015X008-A)
关键词 列车自动驾驶系统 最优预见跟踪控制 速度跟踪 精确停车 舒适性 Automatic Train Operation (ATO) optimal preview tracking control speed tracking precise train stop comfort
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  • 1张建华,贾利民,张锡第.新型模糊预测控制及其在列车自动运行过程中的应用[J].中国铁道科学,1996,17(4):101-109. 被引量:8
  • 2高钦和,王孙安.基于IGPC的时变大时滞系统自适应控制[J].计算机应用,2007,27(6):1508-1509. 被引量:4
  • 3王长林,林颖.列车运行控制技术[M].成都:西南交通大学出版社,2008,72-73.
  • 4佚名.城市轨道交通概论[M].北京:中国劳动社会保障出版社,2009.
  • 5Yasunobu S, Miyamoto S,Ihara H. Fuzzy Control for Automatic Train Operation System [C]//Proceedings of The 4^th IFAC/IFIP/IFRS Int. Conf. on Transportation Systems, 1983:39 -45.
  • 6Oshima H, Yasunobu S,Sekino S. Automatic Train Operation System Based on Predictive Fuzzy Control [C]// Proceedings of International Workshop on Artificial Intelligence for Industrial Applications, 1988: 485-489.
  • 7李会超,翟淼,冯晓云.一种高性能地铁列车运行控制算法研究与仿真[C]//Proceedings of The 7^th World Congress on Intelligent Control and Automation. ChongQing, China: 2008:25-27.
  • 8蔡文.物元模型及其应用[M].北京:科学技术文献出版社,1998.122-123.
  • 9ALEXANDER F. A fuzzy knowledge-based system for railway traffic control [ J]. Engineering Applications of Artificial Intelligence, 2000, 13(6) :719 -729.
  • 10SEKINE S, IMASAKI N, ENDO T. Application of fuzzy neural net- work control to automatic train operation and tuning of its control roles [ C]// Proceedings of the 4th IEEE International Conference on Fuzzy Systems and the Second International Fuzzy Engineering Symposium. Piscataway: IEEE, 1995, 4: 1741- 1746.

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