基于轴距预瞄的虚拟轨道列车主动悬架控制策略

针对虚拟轨道列车垂向振动问题,基于轴距预瞄原理设计了一种列车主动悬架控制策略.首先,考虑线性滤波白噪声路面不平度激励,建立了列车—路面耦合振动模型；其次,结合列车轴距预瞄信息,利用线性二次型高斯(Linear Quadratic Gaussian,LQG)控制理论设计了列车主动悬架LQG控制器,并基于自适应粒子群算法(Adaptive Particle Swarm Optimization,APSO)对控制器的权重系数进行优化；最后,研究了列车在随机路面和脉冲路面激励作用下的垂向振动特性.仿真结果表明,本文所设计的列车主动悬架控制策略能明显降低列车在随机路面和脉冲路面激励作用下各节车体的垂向振动,且针对不同等级路面和车速工况,均有良好的鲁棒性,有效提高了虚拟轨道列车的乘坐舒适性.

Active Suspension Control Strategy of Virtual Rail Train Based on Wheelbase Preview

For the vertical vibration problems of virtual track train, an active suspension control strategy is designed based on wheelbase preview principle. Firstly, the vertical vibration model of the train coupled with the stochastic uneven road is established, where the road is treated as the time domain excitation of road unevenness in the linear filter white noise method. Secondly, the active suspension controller of the train is developed using the linear quadratic Gaussian (LQG) control theory based on the train wheelbase preview information. The adaptive particle swarm optimization (APSO) is used to optimize the weighting coefficients of the developed controller. Finally, the vertical dynamics of the train under the excitation of random and pulse roads is studied. The simulation results show that the control strategy reduces the vertical vibration of each vehicle body of the train under road excitations, and has good robustness against with different road grades and train speeds, and the ride comfort of the train is improved.