Motion simulation platforms (MSPs) are widely used to generate driving/flying motion sensations for the users. The MSPs have a restricted workspace area due to the dynamical and physical restrictions of the Motion Platforms active joints as well as the physical limitations of its passive joints. The motion cueing algorithm (MCA) is the reproduction of the motion signal including linear accelerations and angular velocities. It aims to simultaneously respect the MSP's workspace limitations and make the same motion feeling for the user as a real vehicle. The Classical washout filter (WF) is a well-known type of MCA. The classical WF is easy to set-up, offers a low computational burden and high functionality but has some major drawbacks such as fixed WF parameters tuned according to worst-case scenarios and no consideration of the human vestibular system. As a result, adaptive WFs were developed to consider the human vestibular system and enhance the efficiency of the method using time-varying filters. The existing adaptive WFs only cogitate the boundaries of the end-effector in the Cartesian coordinate space as a substitute for the active and passive joints limitations, which is MSP's main limiting factor. This conservative assumption reduces the available workspace area of the MSP and increases the motion sensation error for the MSPs user. In this study, a fuzzy logic-based WF is developed, to consider the dynamical and physical boundaries of the active joints as well as the physical boundaries of the passive joints. A genetic algorithm is used to select the membership functions’ values of the active and passive joints’ boundaries. The model is designed using MATLAB /Simulink and the outcomes demonstrate the efficiency of the proposed method versus existing adaptive WFs.

中文翻译：

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考虑关节限制的运动仿真平台基于模糊逻辑的自适应冲刷滤波器

运动模拟平台 (MSP) 被广泛用于为用户生成驾驶/飞行运动感觉。由于运动平台主动关节的动态和物理限制以及其被动关节的物理限制，MSP 的工作区区域有限。运动提示算法 (MCA) 是运动信号的再现，包括线性加速度和角速度。它旨在同时尊重 MSP 的工作空间限制，并为用户提供与真实车辆相同的运动感觉。经典冲洗过滤器 (WF) 是众所周知的 MCA 类型。经典的 WF 易于设置，提供低计算负担和高功能，但有一些主要缺点，例如根据最坏情况调整的固定 WF 参数，并且没有考虑人类前庭系统。因此，开发了自适应 WF 以考虑人类前庭系统并使用时变滤波器提高方法的效率。现有的自适应 WF 仅在笛卡尔坐标空间中考虑末端执行器的边界，以替代主动和被动关节限制，这是 MSP 的主要限制因素。这种保守的假设减少了 MSP 的可用工作区，并增加了 MSP 用户的运动感觉误差。在这项研究中，开发了一种基于模糊逻辑的 WF，考虑主动关节的动力学和物理边界以及被动关节的物理边界。遗传算法用于选择主动和被动关节边界的隶属函数值。该模型是使用 MATLAB/Simulink 设计的，结果证明了所提出的方法与现有自适应 WF 相比的效率。