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基于加速度反馈增强的旋翼无人机抗风扰控制
Alternative TitleAcceleration Feedback Enhanced Controller forWind Disturbance Rejection of Rotor Unmanned Aerial Vehicle
代波1,2,3; 何玉庆1,2; 谷丰1,2; 王骞翰1; 徐卫良4
Department机器人学研究室
Source Publication机器人
ISSN1002-0446
2020
Volume42Issue:1Pages:79-88
Indexed ByEI
EI Accession number20201608416938
Contribution Rank1
Funding Organization国家重点研发计划(2017YFD0701002, 2018YFC0810100) ; 国家自然科学基金联合基金(U1608253)
Keyword无人机 加速度反馈 抗风扰 参数辨识
Abstract

为了提高无人机的风扰抑制能力,实现无人机安全飞行和精准控制,提出了一种基于加速度反馈的旋翼无人机抗风扰方法.该方法不需要改变原有的控制器结构,在原有的控制器基础上引入角加速度和线加速度反馈,从而实现更快速且更高精度的角度和位置跟踪,提升系统的扰动抑制能力.同时,为了将该算法部署在实际的无人机平台上,提出了一种简单、快速以及适用于加速度反馈的无人机参数辨识方法.结合该方法,将加速度反馈应用到一个六旋翼机上,并在户外持续风和阵风扰动环境下进行了实验验证.实验结果表明,加速度反馈增强型控制器可以有效地抑制这两种风扰,极大地提高了风扰条件下的无人机控制精度.

Other Abstract

In order to enhance the wind rejection ability of unmanned aerial vehicle (UAV) to achieve safe flight and precision control, a wind disturbance rejection method based on acceleration feedback (AF) is proposed for rotor UAV. By introducing linear and angular AF into the original controller, a faster and more accurate attitude and position tracking performance can be obtained without changing the structure of the original controller. Moreover, a simple and fast UAV parameters identification method suitable for acceleration feedback is proposed to deploy AF on a practical UAV system. By using the proposed method, AF is deployed on a hex-rotor and tested in outdoor environment with continuous or gusty winds. The experimental results demonstrate that the AF enhanced controller can suppress these two kinds of wind disturbances effectively and the control accuracy of UAV system is greatly improved.

Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/25879
Collection机器人学研究室
Corresponding Author代波
Affiliation1.中科院沈阳自动化研究所机器人学国家重点实验室
2.中国科学院机器人与智能制造创新研究院
3.中国科学院大学
4.奥克兰大学
Recommended Citation
GB/T 7714
代波,何玉庆,谷丰,等. 基于加速度反馈增强的旋翼无人机抗风扰控制[J]. 机器人,2020,42(1):79-88.
APA 代波,何玉庆,谷丰,王骞翰,&徐卫良.(2020).基于加速度反馈增强的旋翼无人机抗风扰控制.机器人,42(1),79-88.
MLA 代波,et al."基于加速度反馈增强的旋翼无人机抗风扰控制".机器人 42.1(2020):79-88.
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