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针对高速列车运行过程的模型不确定性问题,提出了高速列车的自适应子空间预测控制方法.首先,由列车观测数据集得到高速列车初始子空间预报模型,并利用快速LQ分解方法实现列车观测数据集的在线滑动窗口更新,从而获得列车自适应预报模型;然后,提出了融合当前时刻与过去时刻的加权误差信息的列车模型自适应切换策略,进而设计了高速列车自适应子空间预测控制器;最后,进行了高速列车运行的数值仿真实验,结果表明提出的方法具有较好的列车跟踪性能.
Aiming at the problem of model uncertainty of high-speed train running, an adaptive subspace prediction control method for high-speed train is proposed.Firstly, the initial subspace prediction model of high-speed train is obtained from the train observation dataset, and the fast LQ decomposition method is used to realize the train observation Then the online sliding window of the data set is updated to obtain the train adaptive forecasting model. Then, an adaptive switching strategy of the train model which combines the weighted error information of the current time and the past time is proposed, and then a high speed train adaptive subspace predictive controller Finally, the numerical simulation of high-speed train operation is carried out. The results show that the proposed method has better performance of train tracking.