城轨列车全自动运行系统噪声子空间鲁棒预测控制方法

颜争，兰清群

安徽交通职业技术学院，安徽 合肥   230051

摘要：为建立与实际运行状态更吻合、预测精确度更高的城轨列车全自动运行（fully automatic operation，FAO）系统预测控制模型，根据城轨列车运行的历史数据，综合考虑城轨列车运行过程中的噪声干扰，采用子空间辨识方法得到含噪声的预测控制模型，控制过程不断加入实时采集的数据，迭代模型辨识的历史数据，在线更新模型参数，得到抗干扰能力较强的城轨列车FAO系统噪声子空间鲁棒预测控制器。分别采用幅值为0、2、5、10 km/h的随机干扰噪声，在软件MATLAB中进行仿真试验，对比分析城轨列车FAO系统噪声子空间鲁棒预测器与传统子空间预测控制器的预测精度。结果表明：在随机噪声干扰下，城轨列车FAO系统噪声子空间鲁棒预测控制器的预测精度较高，噪声幅值为10 km/h时预测精度比传统子空间预测控制器提高14.21%。城轨列车FAO系统噪声子空间鲁棒预测控制器可在强干扰运行状态下高精度跟踪给定运行曲线。

关键词：城轨列车；FAO系统；噪声子空间；鲁棒；预测控制

A robust subspace predictive control method on noise of fully autonomous operation system for urban rail train

YAN Zheng, LAN Qingqun

Anhui Communications Vocational & Technical College, Hefei 230051, China

Abstract:Based on the historical operation data of urban rail train and fully considering the impact of noise interference during the operation process, a control model containing noise is constructed by subspace identification method to ensure that it can be more consistent with the actual operating state, and the prediction accuracy is higher. Real-time data is continuously added during the control process to iterate the historical data identified by the model, and the model parameters are updated online to obtain a robust subspace predictive controller with strong anti-interference ability. In MATLAB simulation experiments, noise amplitudes of 0, 2, 5, 10 km/h are set and compared with traditional subspace predictive control methods. The results showed that under the interference of random noise, the robust subspace predictive controller for fully autonomous operation (FAO) system of urban rail trains has a high prediction accuracy. When the noise amplitude is 10 km/h, the prediction accuracy improves by 14.21% compared with the traditional subspace prediction controller. The robust subspace predictive control method on noise of fully autonomous operation system for urban rail trains can achieve high-precision tracking of the expected curve of urban rail trains under strong interference operating conditions.

Keywords: urban rail train; FAO system; noise subspace; robust; predictive control