磁悬浮列车系统的随机最优控制

本文根据磁悬浮列车和车行道的结构特点，将总系统模型按分块原则分成列车、磁执行环节和车行道系统，并在平衡点附近对非线性方程线性化处理，形成末加控制的总系统的状态方程，它是一组考虑外干扰情况下线性时变系统模型。而基于电磁关系原则建立的磁悬浮列车系统模型在末加控制状态下是不稳定的，为了保证列车的行驶舒适性、稳定性及可靠性，承重磁铁与导向磁铁必须加以控制。附加控制方程后，就形成了被控制的总系统的状态方程，从而实现车、磁及车行道模型的有机组合。对于实际工程问题，被控制的总系统的动力学性质由于维数较高，直接计算比较困难，本文采用计算机进行数值仿真，利用随机最优控制理论，对系统悬浮气隙和垂向加速度的变化规律进行了研究，并通过实例给出时变系统的仿真结果。

Random Optimal Control for MAGLEV Train

According to the construction property of MAGLEV and guideway, total system model was divided into vehicle,magnets and guideway system, through linearity of nonlinear equation near balance point, state equation of total system which was not controlled was formed. It was a linear time variable system model. But this uncontrolled model usually was instability. In order to ensure MAGLEBV's ride comfort,stability and reliability, load-bearing iron and guiding iron must be controlled. Considering the controlled equation, the controlled state equation of total system was formed, and vehicle,magnets and guideway system was combined. As engineering issue, the dynamic model of total system often has higher dimensions, so computer was used to simulate the results. Random optimal control theory was used to research suspension gas and vertical acceleration change regularity, and simulation result to a real case alse was given.