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A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks
Wind velocity (strength and direction) is an important parameter for unmanned aerial vehicle (UAV)-based environmental monitoring tasks. A novel wind velocity estimation method is proposed for rotorcrafts. Based on an extended state observer, this method derives the wind disturbance from rotors’ spe...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308789/ https://www.ncbi.nlm.nih.gov/pubmed/30572670 http://dx.doi.org/10.3390/s18124504 |
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author | Wang, Jia-Ying Luo, Bing Zeng, Ming Meng, Qing-Hao |
author_facet | Wang, Jia-Ying Luo, Bing Zeng, Ming Meng, Qing-Hao |
author_sort | Wang, Jia-Ying |
collection | PubMed |
description | Wind velocity (strength and direction) is an important parameter for unmanned aerial vehicle (UAV)-based environmental monitoring tasks. A novel wind velocity estimation method is proposed for rotorcrafts. Based on an extended state observer, this method derives the wind disturbance from rotors’ speeds and rotorcraft’s acceleration and position. Then the wind disturbance is scaled to calculate the airspeed vector, which is substituted into a wind triangle to obtain the wind velocity. Easy-to-implement methods for calculating the rotorcraft’s thrust and drag coefficient are also proposed, which are important parameters to obtain the wind drag and the airspeed, respectively. Simulations and experiments using a quadrotor in both hovering and flight conditions have validated the proposed method. |
format | Online Article Text |
id | pubmed-6308789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63087892019-01-04 A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks Wang, Jia-Ying Luo, Bing Zeng, Ming Meng, Qing-Hao Sensors (Basel) Article Wind velocity (strength and direction) is an important parameter for unmanned aerial vehicle (UAV)-based environmental monitoring tasks. A novel wind velocity estimation method is proposed for rotorcrafts. Based on an extended state observer, this method derives the wind disturbance from rotors’ speeds and rotorcraft’s acceleration and position. Then the wind disturbance is scaled to calculate the airspeed vector, which is substituted into a wind triangle to obtain the wind velocity. Easy-to-implement methods for calculating the rotorcraft’s thrust and drag coefficient are also proposed, which are important parameters to obtain the wind drag and the airspeed, respectively. Simulations and experiments using a quadrotor in both hovering and flight conditions have validated the proposed method. MDPI 2018-12-19 /pmc/articles/PMC6308789/ /pubmed/30572670 http://dx.doi.org/10.3390/s18124504 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Jia-Ying Luo, Bing Zeng, Ming Meng, Qing-Hao A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks |
title | A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks |
title_full | A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks |
title_fullStr | A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks |
title_full_unstemmed | A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks |
title_short | A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks |
title_sort | wind estimation method with an unmanned rotorcraft for environmental monitoring tasks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308789/ https://www.ncbi.nlm.nih.gov/pubmed/30572670 http://dx.doi.org/10.3390/s18124504 |
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