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Automatic carrier landing control for unmanned aerial vehicles based on preview control and particle filtering

机译:基于预览控制和粒子滤波的无人机自动航母着陆控制

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For the carrier-based unmanned aerial vehicles (UAVs), one of the important problems is the design of an automatic carrier landing system (ACLS) that would enable autonomous landing of the UAVs on a moving aircraft carrier. However, the safe autolanding on a moving aircraft is a complex task, mainly because of the deck motion and airwake disturbances, and dimension limitation. In this paper, an innovative ACLS system for carrier-based UAVs is developed, which is composed of the flight deck motion prediction, reference glide slope generation and integrated guidance and control (IGC) modules. The particle filtering method is used to online predict the magnitudes and frequencies of the deck motion, which are used to correct the reference glide slope to achieve minimum dispersion around the ideal touchdown point. An optimal preview control (OPC) scheme is presented for the IGC subsystem design, which fuses the preview information of the reference glide slope, equality constraint of UAV dynamics and performance index function, and predicted information of the carrier deck motion. Simulation results of a nonlinear UAV model show the effectiveness of the ACLS system in carrier autolanding under the deck motion and airwake disturbances. (C) 2018 Elsevier Masson SAS. All rights reserved.
机译:对于基于舰载的无人机(UAV),重要的问题之一是自动航母着陆系统(ACLS)的设计,该系统将使无人机能够自动在移动的航空母舰上着陆。但是,在飞行中的飞机上安全自动着陆是一项复杂的任务,这主要是由于甲板运动和空中苏醒干扰以及尺寸限制。本文研究了一种创新的基于舰载无人机的ACLS系统,该系统由驾驶舱运动预测,参考滑坡生成和集成制导与控制(IGC)模块组成。粒子滤波方法用于在线预测甲板运动的幅度和频率,用于校正参考下滑坡度,以实现理想着陆点附近的最小色散。针对IGC子系统的设计,提出了一种最优的预览控制(OPC)方案,该方案融合了参考滑坡的预览信息,无人机动力和性能指标函数的等式约束以及航母甲板运动的预测信息。非线性无人机模型的仿真结果表明,在甲板运动和空中苏醒干扰下,ACLS系统在舰载自动着陆中的有效性。 (C)2018 Elsevier Masson SAS。版权所有。

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