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首页> 外文期刊>Journal of vibration and control: JVC >Generalized predictive control algorithm of a simplified ground vehicle suspension system
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Generalized predictive control algorithm of a simplified ground vehicle suspension system

机译:简化的地面车辆悬架系统的广义预测控制算法

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摘要

This paper discusses research conducted by the Army Research Laboratory (ARL) - Vehicle Technology Directorate (VTD) on advanced suspension control. ARL-VTD has conducted research on advanced suspension systems that will reduce the chassis vibration of ground vehicles while maintaining tire contact with the road surface. The purpose of this research is to reduce vibration-induced fatigue to the Warfighter as well as to improve the target aiming precision in-theater. The objective of this paper was to explore the performance effectiveness of various formulations of the generalized predictive control algorithm in a simulation environment. Each version of the control algorithm was applied to an identical model subjected to the same ground disturbance input and compared to a baseline passive suspension system. The control algorithms considered include a generalized predictive controller (GPC) with implicit disturbances, GPC with explicit disturbances, and GPC with preview control. The suspension model used was a two-degree-offreedom dof quarter-car model with a given set of vehicle parameters. The performance of the control algorithms were compared based on their effectiveness in controlling peak acceleration and overall average acceleration over a range of vehicle speeds. The algorithms demonstrated significant reductions in the chassis acceleration of the quarter-car model.
机译:本文讨论了由陆军研究实验室(ARL)-车辆技术总局(VTD)进行的有关先进悬架控制的研究。 ARL-VTD已对先进的悬挂系统进行了研究,该系统将减少地面车辆的底盘振动,同时保持轮胎与路面的接触。这项研究的目的是减少战机的振动引起的疲劳,并提高战场上的目标瞄准精度。本文的目的是探索在模拟环境中各种预测控制算法公式的性能有效性。将控制算法的每个版本应用于经受相同地面干扰输入的相同模型,并与基准被动悬挂系统进行比较。考虑的控制算法包括具有隐式干扰的广义预测控制器(GPC),具有显式干扰的GPC和具有预览控制的GPC。使用的悬架模型是具有给定车辆参数集的自由度为2的自由度四分之一汽车模型。根据控制算法在控制车速范围内的峰值加速度和总体平均加速度方面的有效性,比较了这些算法的性能。该算法证明了四分之一车模型的底盘加速度显着降低。

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