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Embedded Fast Nonlinear Model Predictive Control for Micro Aerial Vehicles
Journal of Intelligent & Robotic Systems ( IF 3.1 ) Pub Date : 2021-11-30 , DOI: 10.1007/s10846-021-01522-y
Tiago Nascimento 1, 2 , Martin Saska 2
Affiliation  

Very small size or micro, aerial vehicles are being recently studied due to the large influence of environmental disturbances. The multirotor aerial vehicle (MAV) usually requires control approaches that can guarantee a safe operation. However, limitations with respect to the embedded system (i.e. energy, processing power, memory, etc.) are usually present. In this work, we propose the use of Nonlinear model predictive control (NMPC), which can safely respect input constraints. In contrast, the application of NMPC in embedded systems of Micro-MAV is typically challenging. To solve this issue, we propose a modification on the NMPC called Embedded Fast NMPC that can ensure the implementation of the position controller safely and stably. Micro Multirotor Aerial Vehicles (Micro-MAVs) use low processing power boards. These boards usually rely solely on on-board sensors to perform localization and target detection, which in turn makes this platform suitable for experiments in GNSS-denied environments. We validate our approach with real robot experiments using a Micro-MAV.



中文翻译:

微型飞行器嵌入式快速非线性模型预测控制

由于环境干扰的巨大影响,最近正在研究非常小尺寸或微型的飞行器。多旋翼飞行器 (MAV) 通常需要能够保证安全运行的控制方法。然而,通常存在与嵌入式系统相关的限制(即能量、处理能力、内存等)。在这项工作中,我们建议使用非线性模型预测控制 (NMPC),它可以安全地遵守输入约束。相比之下,NMPC 在 Micro-MAV 嵌入式系统中的应用通常具有挑战性。为了解决这个问题,我们提出了对 NMPC 的修改,称为 Embedded Fast NMPC,可以确保位置控制器的安全稳定实现。微型多旋翼飞行器 (Micro-MAV) 使用低处理能力板。这些板通常仅依靠板载传感器来执行定位和目标检测,这反过来又使该平台适合在拒绝 GNSS 的环境中进行实验。我们通过使用 Micro-MAV 的真实机器人实验验证了我们的方法。

更新日期:2021-12-01
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