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Evaluation on novel architecture for harmonizing manual and automatic flight controls under atmospheric turbulence

机译:在大气湍流下协调手动和自动飞行控制的新型体系结构的评估

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Pilot uncertainty in aircraft response under automatic flight control has triggered aircraft accidents/incidents in the past. This uncertainty compels a pilot to disengage autopilot and switch to manual control. However, the decision to disengage autopilot and when to do it can be difficult: especially if there is not enough time to monitor the cockpit displays, for instance while countering atmospheric turbulence. Against this background, we proposed the "human as a control module" architecture for harmonizing pilot and autopilot controls. The architecture blends pilot maneuver with autopilot control instead of switching between them when simultaneous inputs are given to the aircraft. By automatically adjusting pilot and autopilot control inputs, the architecture avoids overlaps of both control authorities and helps to circumvent the effect of conflicting actions. This paper applies the architecture to the situations of past aircraft incidents which had been caused by the transfer from autopilot control to pilot maneuver after encountering atmospheric turbulence. The effectiveness of the architecture is evaluated via simulation study for the specific incident examples. Furthermore, this paper extends the architecture with an Extended Kalman Filter (EKF) based observer and evaluates its robustness under errors in wind estimation.
机译:过去,自动飞行控制下飞机响应中飞行员的不确定性已经触发了飞机事故/事故征候。这种不确定性迫使飞行员脱离自动驾驶仪并切换到手动控制。但是,决定是否取消自动驾驶仪以及何时进行分离可能会很困难:特别是如果没有足够的时间来监视驾驶舱显示,例如在抵抗大气湍流时。在这种背景下,我们提出了“人为控制模块”架构来协调飞行员和自动驾驶控制。该架构将飞行员操纵与自动驾驶控制融合在一起,而不是在同时输入飞机时在两者之间进行切换。通过自动调整飞行员和自动驾驶控制输入,该架构避免了两个控制机构的重叠,并有助于规避冲突动作的影响。本文将架构应用于过去飞机事故的情况,这些事故是由于遇到大气湍流后从自动驾驶控制转移到飞行员机动而引起的。通过针对特定事件示例的仿真研究评估了体系结构的有效性。此外,本文使用基于扩展卡尔曼滤波器(EKF)的观测器扩展了该体系结构,并评估了在风估计误差下的鲁棒性。

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