基于模式生成的协同相对定位滑模着陆控制器的研制

Rohith Boyinine, Anusna Chakraborty, Rajnikant Sharma, K. Brink
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引用次数: 1

摘要

在本文中,我们开发了一种基于滑模控制律的降落控制器,用于在gps拒绝环境下使用距离测量的相对估计在移动船舶上降落无人机。为了使无人机准确地降落在移动平台的表面上,需要精确地了解相对位置、方向和速度。尽管基于视觉的技术已经被用来解决这些问题,但它们在黑暗或恶劣的天气条件下会失败,而且着陆平台需要始终保持视线。不同的无人驾驶车辆(UVs)之间的合作已经被引入,以帮助估计过程。我们还研究了支持车辆跟随的不同轨迹对定位精度的影响。建立了Matlab/Simulink模拟器,并进行了详尽的仿真,证明了这些轨迹对定位精度的影响。
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Development of Sliding-Mode Landing Controller using Cooperative Relative Localization with Pattern Generation
In this paper, we develop a landing controller based on sliding-mode control law for landing a UAV on a moving ship using relative estimates in GPS-denied environments with range-only measurements. Precise knowledge of relative position, orientation and velocity is required to accurately land an Unmanned Aerial Vehicle (UAV) onto the surface of a moving platform. Although vision-based techniques have been used to previously solve such problems, they fail in dark or hostile weather conditions and also a line of sight is required with the landing platform at all times. Cooperation among different Unmanned Vehicles (UVs) have been introduced to aid the estimation process. We also investigate how different trajectories followed by supporting vehicles effect the localization accuracy. A Matlab/Simulink simulator has been created and exhaustive simulations have been performed that demonstrates the effect of these trajectories on localization accuracy.
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