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Force protection via UGV-UVA collaboration development of control law for vision based target tracking on SUAV

机译:通过UGV-UVA协作开发控制法的力量保护,用于SUAV的基于视觉的目标跟踪

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摘要

The Naval Postgraduate School UAV Laboratory developed a Small Unmanned Aerial Vehicle (SUAV) equipped with a Vision Based Target Tracking (VBTT) system as part of its Tactical Network Topology field experimentation program. The VBTT system includes a miniaturized gimbaled camera that allows autonomous target tracking while providing concurrent estimates of target motion including its position, velocity and heading. Using the current control law, the speed of convergence and the range-holding performance have been found to deteriorate as target speed increases. The aim of this thesis is to elaborate on the existing control law in order to achieve better performance. Employing a new and novel algorithm from the Lyapunov Stability Analysis, for the purpose of adjusting the feedback gain, is proposed in this thesis; to that end a control law with adjustable gain can be easily implemented based on UAV-Target kinematics to optimize UAV performance. The performance of the newly adjustable gain control law is tested in both SIMULINK model and Hardware-In-the-Loop simulations to verify any improvement in performance over the constant gain control law. Principal results offer improved SUAV target-tracking performance with no additional hardware costs.
机译:海军研究生院无人机实验室开发了一种小型无人机(SUAV),该无人机配备了基于视觉的目标跟踪(VBTT)系统,作为其战术网络拓扑现场实验计划的一部分。 VBTT系统包括一个微型万向架摄像机,该摄像机可以进行自主目标跟踪,同时提供目标运动的并发估计,包括其位置,速度和航向。使用当前的控制定律,发现收敛速度和范围保持性能会随着目标速度的增加而降低。本文的目的是阐述现有的控制律,以取得更好的性能。本文提出了一种基于Lyapunov稳定性分析的新颖算法,用于调整反馈增益。为此,可以基于无人机目标运动学轻松实现具有可调增益的控制律,以优化无人机性能。新可调增益控制定律的性能在SIMULINK模型和硬件在环仿真中均经过测试,以验证性能在恒定增益控制定律之上的任何改进。主要结果提供了改进的SUAV目标跟踪性能,而没有额外的硬件成本。

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    Lee Shay Liang.;

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  • 年度 2007
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