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An Empirical Human Controller Model for Preview Tracking Tasks

机译:用于预览跟踪任务的经验型人工控制器模型

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摘要

Real-life tracking tasks often show preview information to the human controller about the future track to follow. The effect of preview on manual control behavior is still relatively unknown. This paper proposes a generic operator model for preview tracking, empirically derived from experimental measurements. Conditions included pursuit tracking, i.e., without preview information, and tracking with 1 s of preview. Controlled element dynamics varied between gain, single integrator, and double integrator. The model is derived in the frequency domain, after application of a black-box system identification method based on Fourier coefficients. Parameter estimates are obtained to assess the validity of the model in both the time domain and frequency domain. Measured behavior in all evaluated conditions can be captured with the commonly used quasi-linear operator model for compensatory tracking, extended with two viewpoints of the previewed target. The derived model provides new insights into how human operators use preview information in tracking tasks.
机译:现实生活中的跟踪任务通常向人工控制器显示有关未来跟踪的预览信息。预览对手动控制行为的影响仍然相对未知。本文提出了一个用于实验跟踪的通用算子模型,该模型是根据实验测量得出的。条件包括追踪追踪,即没有预览信息,以及追踪1秒的追踪。受控元件动力学在增益,单积分器和双积分器之间变化。应用基于傅立叶系数的黑匣子系统识别方法后,在频域中推导该模型。获得参数估计值以评估时域和频域模型的有效性。可以使用用于补偿跟踪的常用准线性算子模型捕获在所有评估条件下的测量行为,并用预览目标的两个视点进行扩展。派生模型为操作员如何在跟踪任务中使用预览信息提供了新的见解。

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