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采用冗余通信系统的重型无人机推力矢量控制。

Thrust Vectoring Control for Heavy UAVs, Employing a Redundant Communication System.

机构信息

Computer Vision and Aerial Robotics Group, Centre for Automation and Robotics (CAR), Universidad Politécnica de Madrid (UPM-CSIC), 28006 Madrid, Spain.

Wake Engineering Company, 28906 Getafe, Spain.

出版信息

Sensors (Basel). 2023 Jun 14;23(12):5561. doi: 10.3390/s23125561.

DOI:10.3390/s23125561
PMID:37420728
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10303676/
Abstract

Recently, various research studies have been developed to address communication sensors for Unmanned Aerial Systems (UASs). In particular, when pondering control difficulties, communication is a crucial component. To this end, strengthening a control algorithm with redundant linking sensors ensures the overall system works accurately, even if some components fail. This paper proposes a novel approach to integrate several sensors and actuators for a heavy Unmanned Aerial Vehicle (UAV). Additionally, a cutting-edge Robust Thrust Vectoring Control (RTVC) technique is designed to control various communicative modules during a flying mission and converge the attitude system to stability. The results of the study demonstrate that even though RTVC is not frequently utilized, it works as well as cascade PID controllers, particularly for multi-rotors with mounted flaps, and could be perfectly functional in UAVs powered by thermal engines to increase the autonomy since the propellers cannot be used as controller surfaces.

摘要

最近,已经开发出各种研究来解决无人飞行器 (UAS) 的通信传感器问题。特别是在考虑控制困难时,通信是一个关键组成部分。为此,通过冗余连接传感器来增强控制算法可以确保整个系统准确运行,即使某些组件出现故障。本文提出了一种将多个传感器和执行器集成到重型无人飞行器 (UAV) 的新方法。此外,还设计了一种先进的鲁棒推力矢量控制 (RTVC) 技术,用于在飞行任务期间控制各种通信模块,并使姿态系统收敛到稳定状态。研究结果表明,即使 RTVC 不常使用,它的效果与串级 PID 控制器一样好,特别是对于带有襟翼的多旋翼,并且在由热发动机驱动的无人机中也可以完美运行,因为螺旋桨不能用作控制器表面,从而增加了自主性。

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WILD HOPPER: A heavy-duty UAV for day and night firefighting operations.Wild Hopper:一款用于昼夜灭火作业的重型无人机。
Heliyon. 2022 May 31;8(6):e09588. doi: 10.1016/j.heliyon.2022.e09588. eCollection 2022 Jun.
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Fast Multi-UAV Path Planning for Optimal Area Coverage in Aerial Sensing Applications.
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