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Robust system state estimation for active suspension control in high-speed tilting trains

机译:高速摆式列车主动悬架控制的鲁棒系统状态估计

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摘要

The interaction between the railway vehicle body roll and lateral dynamics substantially influences the tilting system performance in high-speed tilting trains, which results in a potential poor ride comfort and high risk of motion sickness. Integrating active lateral secondary suspension into the tilting control system is one of the solutions to provide a remedy to roll?lateral interaction. It improves the design trade-off for the local tilt control (based only upon local vehicle measurements) between straight track ride comfort and curving performance. Advanced system state estimation technology can be applied to further enhance the system performance, i.e. by using the estimated vehicle body lateral acceleration (relative to the track) and true cant deficiency in the configuration of the tilt and lateral active suspension controllers, thus to further attenuate the system dynamics coupling. Robust H-inf filtering is investigated in this paper aiming to offer a robust estimation (i.e. estimation in the presence of uncertainty) for the required variables, In particular, it can minimise the maximum estimation error and thus be more robust to system parametric uncertainty. Simulation results illustrate the effectiveness of the proposed schemes.
机译:铁路车辆车身侧倾和横向动力学之间的相互作用会极大地影响高速倾斜列车中的倾斜系统性能,从而导致潜在的差的乘坐舒适性和晕车的高风险。将主动侧向次要悬架集成到倾斜控制系统中是解决侧倾相互作用的一种解决方案。它改善了在直线行驶舒适性和弯曲性能之间进行局部倾斜控制(仅基于本地车辆测量)的设计折衷。可以应用先进的系统状态估计技术来进一步增强系统性能,即通过使用估计的车身横向加速度(相对于轨道)和倾斜和横向主动悬架控制器的配置中的真实倾斜度不足,从而进一步衰减系统动力学耦合。本文研究了鲁棒的H-inf滤波,旨在为所需变量提供鲁棒的估计(即在存在不确定性的情况下进行估计),特别是它可以最大程度地减小最大估计误差,从而对系统参数不确定性更鲁棒。仿真结果说明了所提方案的有效性。

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