基于模糊调优的自适应运动提示算法改善人的感觉

Tang Zhiyong, Ma Hu, Pei Zhongcai, Z. Jinhui
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引用次数: 5

摘要

运动线索算法(MCA)作为飞行模拟器的关键技术之一,对于在物理限制条件下生成逼真的运动和相似的人类感知具有重要作用。经典的洗出算法虽然是最流行的MCAs,但它存在一些缺点,包括原始信号失真、线索运动错误、工作空间使用不当和人的感觉错误。为了克服这些问题,最大限度地减少实际飞行与模拟器之间的人的感觉误差,同时在运动约束条件下更有效地利用平台,本文提出了一种基于模糊逻辑在线整定的信号误差补偿方法。基于位移、工作空间限制和感知比力误差的模糊整定逻辑控制器。该方法还包含一个非线性缩放因子来调节输入信号的幅度,并使用倾斜限幅器的部分范围缩放来克服不连续运动。仿真分析结果表明,该方法在降低人的感觉误差,满足高保真度要求的同时,在物理限制下更有效地利用平台工作空间,实现了逼真的运动效果。
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Adaptive motion cueing algorithm based on fuzzy tuning for improving human sensation
As one of the key technologies of flight simulator, motion cueing algorithm (MCA) plays a great role in regenerating realistic motion and the similar human perception within physical limitations. Although it is the most popular MCAs, classic washout algorithm has some drawbacks, including distortion of the original signal, false cue motions, poor usage of the workspace and wrong human sensation. In order to overcome these problems and minimize human sensation error between the actual flight and simulator while exploiting the platform more efficiently within the motion constraints, this paper proposed a new method which adopt signal error compensators based on fuzzy logic online tuning. And the fuzzy tuning logic controller based on displacement, workspace limitation and the sensed specific force error. The proposed method also contains a non-linear scaling factor to adjust the amplitude of the input signal and uses partial range scaling of the tilt rate limiter to overcome the discontinuous movement. After simulating and analyzing, it shows the superiority of the proposed MCA as it decreases human sensation error to meet high fidelity and exploit platform workspace more efficiently within physical limitations to deliver realistic motion.
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