数据驱动的高速列车子空间预测控制

Predictive Control of High-speed Train Based on Data Driven Subspace Approach

随着列车运行速度的提高,列车与接触网、轨道、空气的动力作用加剧,给高速列车的建模与控制提出更高的要求。本文提出数据驱动的高速列车子空间预测控制方法:构建基于状态框架的高速列车多变量动力学系统;由输入输出数据设计高速列车的子空间预报模型;详细分析高速列车子空间预测控制器的设计方法,并给出相应的预测控制算法。高速列车的数值仿真实验结果证明所提出控制方法的有效性。

Along with raising of train speeds, dynamic interaction between train and catenary, track and air intensifies, which sets high requirements for modeling and control of high-speed trains. In this paper, the predictive controller, based on data driven subspace approach, was designed for high-speed trains. The high-speed train multivariate dynamic system was established on the basis of the state space model. The high-speed train predictive subspace model was designed from input and output data. The method of designing the predictive controller was analyzed in detail and the predictive control algorithm was given. Through numerical simulation of high-speed trains, the effectiveness of the proposed control method is proved.