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Active Suspension System for Passenger Vehicle using Active Force Control with Iterative Learning Algorithm ud

机译:主动式主动控制与迭代学习算法的乘用车主动悬架 ud

摘要

The paper describes the practical implementation of a new hybrid control method to a vehicle suspension system using Active Force Control (AFC) with Iterative Learning (IL) and proportional-integralderivative (PID) control strategy. The overall control system essentially comprises three feedback control loops to cater for a number of specific tasks; the innermost loop for the force tracking of the pneumatic actuator using a PI controller, the intermediate loops implementing AFC with IL algorithm strategy for the compensation of the disturbances, and the outermost loop using a PID controller for the computation of the desired force. A number of experiments were carried out on a physical quarter car test rig with hardware-in-the-loop simulation (HILS) feature that fully incorporates the theoretical elements. The performance of the proposed control method was evaluated and benchmarked to examine the effectiveness of the system in suppressing the vibration effect. It was found that the experimental results demonstrate the superiority of the active suspension system with AFCIL scheme compared to the PID and passive counterparts. The vertical body acceleration and displacements are clearly reduced, thereby implying that the ride comfort aspect of the system is improved via the proposed control scheme.
机译:本文介绍了一种新的混合动力控制方法在车辆悬架系统上的实际实现方法,该方法使用具有迭代学习(IL)和比例积分微分(PID)控制策略的主动力控制(AFC)。整个控制系统实质上包括三个反馈控制回路,以满足许多特定任务。最里面的回路用于使用PI控制器跟踪气动执行器的力,中间回路使用带有IL算法策略的AFC来实现对干扰的补偿,最外面的回路使用PID控制器来计算所需的力。在具有物理在环仿真(HILS)功能的物理四分之一汽车测试台上进行了许多实验,这些功能完全结合了理论要素。对所提出的控制方法的性能进行了评估和基准测试,以检验该系统在抑制振动影响方面的有效性。实验结果表明,与PID和被动对等系统相比,采用AFCIL方案的主动悬挂系统具有优越性。车身的垂直加速度和位移明显减小,这意味着通过建议的控制方案可改善系统的乘坐舒适性。

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