高速与城市轨道列车多模态非线性运行控制过程建模与辨识

This proposal studies the modeling and identification methods for a class of multi-modal nonlinear operation process of high-speed trains and urban railway trains in a control oriented way. Due to the complexity of the train operation with nonlinear dynamics and time-varying process parameters, the operation process of the railway trains that have multiple operating modes render multi-modal nonlinear characteristics. It is impossible to use a fixed model to characterize the entire process and meet the requirement of high control accuracy. The research on the modeling and identification methods for this class of multi-modal nonlinear operation process has great significance on the safety and the control accuracy improvement of railway train operation. The main contents include (1) Use the Linear Parameter-Varying (LPV) modelling approach, study the multi-model methods for the multi-modal nonlinear operation process of high speed trains and urban railway trains; (2) On the basis of the mechanism modeling and statistical modeling methods, solve the problems of the typical nonlinear dynamics modeling; (3) Further use the filtering compensation technique, along with the decomposition technique and the decoupling technique, study the new multi-innovation identification methods for the local multi-input multi-output sub-model of high-speed trains with colored noises and missing data; (4) build the simulation and experiment platform, develop the practical software tools from the theoretic methods. This proposal belongs to applied basic researches and will propel the development of key technologies of railway train operation.

从面向控制的角度，研究复杂运行环境下高速与城市轨道列车多模态非线性运行过程的建模和辨识新方法。列车运行环境复杂，过程存在多类干扰。多工况、非线性动态以及过程时变参数令运行控制过程呈现多模态非线性特征。单一模型难以刻画该运行控制过程，无法满足高性能控制需求。研究多模型建模方法与辨识方法能够为列车安全运行与精确控制提供模型化支撑。本项目拟研究内容包括：(1)借助线性变参数模型方法，研究能够刻画高速与城轨列车复合多模态运行控制过程的多模型建模方法；(2)基于机理建模与统计建模方法，研究列车运行过程典型非线性动态的建模问题；(3)结合分解耦合技术，应用滤波补偿技术和多新息辨识原理，研究有色噪声和丢失数据环境下的高速列车多输入多输出局部子模型辨识新方法，提高建模精度；(4)搭建仿真与验证平台，开发与理论方法对应的工程应用软件工具。本项目偏向应用基础研究，成果将推动轨道交通列车运行控制关键技术的发展。