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首页> 外文期刊>International Journal of Control, Automation, and Systems >Improvement of Shipboard Landing Performance of Fixed-wing UAV Using Model Predictive Control
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Improvement of Shipboard Landing Performance of Fixed-wing UAV Using Model Predictive Control

机译:使用模型预测控制改进固定翼UAV的船舶着陆性能

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摘要

This paper investigates automatic UAV carrier landing using model predictive control that considers carrier deck motions. With dynamic models of a medium-altitude, long-endurance UAV and an aircraft carrier, the proposed guidance and control approach takes the relative geometry between the UAV and the carrier deck into account for safer shipboard landings. Automatic carrier landing is performed sequentially by two types of control systems. A linear quadratic regulator with an integral term is applied up to a few seconds before touchdown followed by a model predictive controller. At this time, optimal control input sequences over a certain time horizon are calculated in real time by predicting the motions of the carrier deck and the UAV. Numerical simulations are performed for a UAV and a carrier with heave motion to verify the feasibility of the proposed approach.
机译:本文研究了采用模型预测控制来调查自动无人机载波着陆,以考虑运营商甲板运动。 利用中高度,长耐力无人机和航空母舰的动态模型,所提出的指导和控制方法考虑到更安全的船上着陆,从UAV和承运人牌之间采用相对几何。 自动载波着陆由两种类型的控制系统顺序进行。 具有整体项的线性二次调节器可在触摸触之前施加几秒钟,然后应用于模型预测控制器。 此时,通过预测载体甲板和UAV的运动来实时计算一定时间范围内的最佳控制输入序列。 对UAV和具有升降运动的载波执行数值模拟以验证所提出的方法的可行性。

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