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GPC-Based Deck Motion Estimation for Autonomous Ship Deck Landing of an Unmanned Aircraft

机译:基于GPC的甲板运动估计,用于无人驾驶飞机的自主船甲板降落

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Landing an aircraft on a ship deck in high sea states can be challenging due to the risk for adverse interactions between the moving ship deck and aircraft components. When deck motion is significant, aircraft must sometimes wait for an extended duration until a calm period is detected to land safely. This paper presents a deck motion estimation (DME) algorithm that can decrease landing times. The DME algorithm runs in real-time allowing for fully autonomous ship deck landings without a human operator in the loop. The proposed solution uses generalized predictive control to predict future ship deck states based on prior observations. A landing is commanded when ship deck states are predicted to be within quiescent bounds for a pre-determined prediction horizon in which a safe landing could be completed. Monte-Carlo simulations utilizing ship state data show that the deck motion estimation can accurately predict quiescent landing periods. Further, flight test experiments have demonstrated the feasibility of implementing the system for an unmanned aircraft.
机译:由于移动船甲板和飞机部件之间的不利相互作用的风险,在高海域的船甲板上落地一架飞机可能是挑战。当甲板运动很重要时,飞机必须等待延长持续时间,直到检测到平静的时期安全地降落。本文介绍了可以减少登陆时间的甲板运动估计(DME)算法。 DME算法实时运行,允许在循环中没有人为操作员的完全自主船甲板着陆。所提出的解决方案采用广义预测控制根据现有观察来预测未来的船舶甲板状态。当船舶甲板状态预测在静止的预测地平线上时,命令着陆时命令着陆。利用船舶状态数据的Monte-Carlo仿真显示甲板运动估计可以准确地预测静态着陆周期。此外,飞行试验实验表明,为无人驾驶飞机实施系统的可行性。

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