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Nonlinear speed estimation of a GPS-free UAV

机译:无GPS无人机的非线性速度估计

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摘要

In this article, the problem of robust state observer design for a class of unmanned aerial vehicles (UAVs) is addressed. A prototype four-rotors helicopter robot for indoors and outdoors applications is considered: the drone is not equipped with GPS related devices, so we describe a strategy to estimate its translational velocity vector based on acceleration, angles and angular speeds measurements only. Since the linearised system is non-observable at the equilibrium point, a nonlinear observability verification is performed for persistently exciting trajectories. A global exponential solution to this open problem is provided in the framework of adaptive observation theory when exact measurements are available. A modified observer is presented to enhance velocity estimation robustness in the realistic case of noisy measurements. The results are compared with a classical estimation strategy based on the extended Kalman filter to test the algorithm's performance.
机译:在本文中,解决了一类无人机的鲁棒状态观测器设计问题。考虑了适用于室内和室外应用的原型四旋翼直升机机器人:该无人机未配备GPS相关设备,因此我们描述了一种仅根据加速度,角度和角速度测量来估计其平移速度矢量的策略。由于线性化系统在平衡点不可观察,因此对持续激发的轨迹进行了非线性可观察性验证。当精确测量可用时,在自适应观测理论的框架中提供了针对此开放问题的全局指数解决方案。提出了一种改进的观察器,以提高在嘈杂测量的实际情况下速度估计的鲁棒性。将结果与基于扩展卡尔曼滤波器的经典估计策略进行比较,以测试算法的性能。

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