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为了在保证行车安全的前提下,提高列车的横向平稳性能,提出一种基于天棚原理的列车横向半主动悬挂系统,并建立了半主动悬挂非线性神经网络控制模型,设计了神经辨识器和控制器.仿真计算和实测结果显示:与不施加控制时相比,半主动悬挂系统采用神经网络控制时车体的横向加速度峰值明显下降,横向平稳性明显改善,横向平稳性指标(W值)在仿真和实测状况下分别改善了9.04%和15.9%.
In order to improve the transverse stability of the train under the premise of ensuring traffic safety, a semi-active traverse semi-active suspension system based on sky-ceiling principle is proposed and a semi-active suspension nonlinear neural network control model is established. The neural recognizer and control The simulation results and the measured results show that the peak value of lateral acceleration of the semi-active suspension system decreases obviously when the semi-active suspension system is controlled by the neural network compared with that without control, and the horizontal stability is obviously improved. The horizontal stability index (W value) Under the condition of simulation and experiment, it improved by 9.04% and 15.9% respectively.