无人驾驶城轨车辆运动控制方法研究

The properties of the unmanned urban rail vehicle controller directly affect the safety, stability and comfort of the train operation, so the research on motion control approaches for unmanned urban rail vehicles has important scientific significances. In view of problems including the unitary of the intelligent algorithms applied in the unmanned urban rail vehicles control theory, the lack of researches on restrictive relation between train operation stability and vehicle traction control and the absence of trains collaborative control study in the conditions of Internet of Things, the effective motion control approach is explored for unmanned urban rail vehicles with properties of highly nonlinearity, strong coupling and complicated working conditions. Firstly, integrated intelligent control algorithm is adopted to establish multi-objective traction control strategy to implement the urban rail operation requirements including safety, stationarity, and rapidity and so on. Considering internal and external disturbance and vibration parameters uncertainty, robust controller is designed to reduce the vehicle vibration. Then, taking into account the mutual restriction relationship between vehicle traction and smooth operation, the coupling relationship model of the vehicle traction control and vibration control is established to study the coupling mechanism and the parameters matching relationship. Finally, the hierarchical distributed control architecture in the conditions of Internet of Thing is established in order to achieve effective and safe train collaborative control during running. The anticipated research results can provide theoretical and technical support for research and application of unmanned urban rail vehicle theory.

无人驾驶城轨车辆控制器性能优劣直接影响车辆运行的安全性、稳定性和舒适性，所以研究其运动控制方法具有重要的科学意义。本申请主要针对无人驾驶城轨车辆控制理论研究中智能控制算法应用比较单一、车辆运行稳定性和牵引控制间制约关系研究较少，以及物联网条件下车辆协同控制研究缺乏等问题，探索解决具有高度非线性、强耦合和复杂工况的无人驾驶城轨车辆运动控制的有效方法。首先，采用集成智能控制算法建立多目标牵引控制策略，实现城轨车辆安全、平稳、快速等运行要求；考虑车辆振动模型内-外不确定性和非线性，引入鲁棒控制理论减小车辆横、垂向振动。其次，考虑无人驾驶城轨车辆牵引与运行平稳性之间的相互制约关系，建立车辆牵引与振动控制耦合关系模型，研究其耦合机理和参数匹配关系。最后，搭建物联网条件下分层分布控制体系结构，实现列车高效安全运行的协同控制。预期研究成果可为提高无人驾驶城轨车辆控制理论研究和应用水平提供理论与技术支撑。

对无人驾驶城轨车辆运动控制方法进行研究，首先通过城轨车辆运动学分析，采用集成智能控制算法实现城轨车辆多目标牵引控制。建立了以能耗、准时性、停车精度以及舒适性为指标的城轨列车运行多目标模型，设计了自适应模糊PID速度控制器，仿真结果表明了自适应模糊PID控制具有较好地鲁棒性以及更理想的控制效果，能满足列车运行的性能需求；二是在分析车辆横向/垂向振动机理的基础上，采用鲁棒控制算法来抑制车辆振动，提高无人驾驶城轨车辆运行的平稳性。建立了轨道车辆横向半主动悬挂控制模型，并提出了一种半主动悬挂鲁棒非脆弱H∞控制器的设计方法，仿真结果表明了该控制器能够有效保证轨道车辆的乘坐舒适性；三是研究了城轨车辆牵引控制和运行平稳性间的相互制约关系，探索车辆牵引/振动控制耦合关系模型。构建了车辆牵引控制策略模型与城轨车辆整车模型，详细地分析了外界激扰对车辆振动的影响；最后利用物联网技术集成的优势，建立了物联网条件下无人驾驶城轨车辆协同控制分层递阶结构模型，为无人驾驶城轨车辆协同控制的实现提供了一种有效途径。研究成果提高了无人驾驶城轨车辆的控制理论研究和应用水平，另外可以为轨道交通领域进行无人驾驶技术的理论和应用研究提供重要借鉴。