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考虑高速列车的安全性、准时性和节能环保的要求,设计列车运行的目标曲线;根据列车运行过程随机性的特点,结合滑模预测控制强鲁棒性的优点设计了ATO的控制器。首先用模糊聚类算法对系统输入输出数据进行快速分类,应用最小二乘法辨识出相应的线性子模型作为预测模型;其次,在考虑准时性的基础上采用节能优化理论设计列车运行目标曲线,作为控制系统的参考输入;最后设计滑模预测控制器,利用极点配置方法设计渐进稳定的滑模面,有效克服抖振现象。以CRH2-300型列车为研究对象进行仿真分析,结果表明,滑模预测控制能有效克服干扰信号,且能实现精确跟随所设计的目标曲线;验证了该算法应用到ATO中的有效性和可行性。
Considering the safety, punctuality and requirements of energy-saving and environmental protection of high-speed trains, the target curve of train operation is designed. According to the characteristics of train running process and the strong robustness of sliding mode predictive control, ATO controller is designed. Firstly, the fuzzy clustering algorithm is used to classify the input and output data of the system quickly, and the corresponding linear sub-models are identified as the prediction models by using the least square method. Secondly, based on the punctuality, the energy-saving optimization theory is used to design the train operation target curve. Control system reference input. Finally, a sliding mode predictive controller is designed to design a gradual and stable sliding mode surface by using the pole placement method to effectively overcome the chattering phenomenon. The simulation analysis of the CRH2-300 train is carried out. The results show that the sliding mode predictive control can effectively overcome the interference signal and can accurately follow the designed target curve. The validity and feasibility of the algorithm applied to the ATO is verified Sex.