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Manual Control with Pursuit Displays: New Insights, New Models, New Issues

机译:追踪显示的手动控制:新见解,新模型,新问题

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摘要

Mathematical control models are widely used in tuning manual control systems and understanding human performance. The most common model, the crossover model, is severely limited, however, in describing realistic human control behaviour in relevant control tasks as it is only valid for tracking with a compensatory display. This paper first discusses the state-of-the-art in modelling human control in tracking with pursuit displays. It is shown that, although both tasks seem very similar, the separate presentation of target and system output signals allows operators to adopt a huge variety in control strategies, which makes the development of a universal model for pursuit control a challenge. Two recent models are then described which can act as precursors to such a universal model. Third, system identification choices and issues are discussed for pursuit tracking tasks. Finally, it is argued that it is inevitable that time-varying rather than time-invariant methods are needed to properly describe human behaviour in the pursuit tracking task, as skilled operators will learn to characterize the probabilistic nature of the task, which cannot be captured in a single, linear, time-invariant model.
机译:数学控制模型广泛用于调整手动控制系统和理解人员性能。但是,在描述相关控制任务中的实际人为控制行为时,最常见的模型(交叉模型)受到了严格限制,因为它仅对带有补偿性显示的跟踪有效。本文首先讨论了跟踪追踪显示中的人类控制建模的最新技术。结果表明,尽管两个任务看起来非常相似,但目标信号和系统输出信号的单独表示使操作员可以采用多种控制策略,这使得开发通用的追赶控制模型成为一个挑战。然后描述了两个最新模型,它们可以作为这种通用模型的前身。第三,讨论了跟踪追踪任务的系统识别选择和问题。最后,有争议的是,不可避免地需要时变方法而不是时不变方法来正确描述追踪跟踪任务中的人类行为,因为熟练的操作员将学会表征任务的概率性质,这无法捕获在单个线性时不变模型中

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