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Ride Quality Improvement for High-Speed Railway Based on D-Type Iteration Learning Control

机译:基于D型迭代学习控制的高速铁路乘坐质量改进

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Though differential-type (D-type) control method and iteration learning control (ILC) are both classic control strategy, ILC is rarely used for lateral control of trains. In this paper, a D-type ILC is proposed to suppress the lateral vibration of train body and improve ride quality. First, the dynamic model of lateral and yaw motions for train body is introduced, where external disturbances caused by bogies are considered. Based on the repeatability of train operation, a iteration learning controller in combination with D-type control method is employed to better suppress the lateral motions of train body. Unlike traditional PID controller, the D-type iterative learning controller can make good use of the train’s repeatability to adjust the input force to the actuator. Then, the convergence condition is analyzed to ensure the rationality of the proposed algorithm. In order to verify the effectiveness of proposed controller, the co-simulation of a full-scale train model with German high interference track irregularities in SIMPACK and the control flow in SIMULINK is established to evaluate the effectiveness by comparing with a open-loop system.
机译:虽然差分型(D型)控制方法和迭代学习控制(ILC)都是经典控制策略,但ILC很少用于列车的横向控制。本文提出了一种D型ILC以抑制火车体的横向振动并提高乘坐质量。首先,介绍了火车体横向和偏航运动的动态模型,其中考虑了由传导术引起的外部干扰。基于列车操作的可重复性,采用与D型控制方法结合的迭代学习控制器来更好地抑制火车体的横向运动。与传统的PID控制器不同,D型迭代学习控制器可以良好地利用火车的可重复性来调整对致动器的输入力。然后,分析收敛条件以确保所提出的算法的合理性。为了验证所提出的控制器的有效性,建立了使用德国高干扰轨道不规则性的全尺度列车模型的共模,并建立了与Simulink中的控制流程,以评估了与开环系统相比的有效性。

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