Performance Evaluation of Flight Control Strategies for a Pesticide-Carrying Unmanned Aerial Vehicle

The efficient transportation of liquids by unmanned aerial vehicles (UAVs) is of utmost importance in various autonomous missions, including firefighting and field spraying. Nevertheless, liquid sloshing during transportation can lead to undesirable effects such as instability, unwanted forces, position error, and increased control effort resulting in inefficient power utilization and payload constraints. To mitigate the effects of Chlorpyrifos (pesticide) sloshing, a Lagrangianbased dynamic model of UAV and resulting slosh was developed. Using SMD analogy, sloshing and the dynamic equation of the quadcopter was modeled based on the geometry of the liquid container. An effective classical control algorithm for a liquid carrier quadcopter is presented which has been extensively investigated, validated, and compared. Simulations based on Coppelia V-rep are also presented to investigate the real time implementation of the proposed system. The results demonstrate a decrease in chlorpyrifos slosh amplitude and intuitively, a reduction in the control effort. These findings have significant implications for improving the quality of quadcopter control in various real-world applications

Authors

Institutions

Publication Details

Published
2025-08-10
DOI
https://doi.org/10.1109/wrcsara68202.2025.11195009
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Performance Evaluation of Flight Control Strategies for a Pesticide-Carrying Unmanned Aerial Vehicle

Xiangdong Meng, Haoliang Xu, Muntazir Hussain, Rashid Khan et al.
UAV Applications and Optimization
article

Performance Evaluation of Flight Control Strategies for a Pesticide-Carrying Unmanned Aerial Vehicle

Xiangdong Meng, Haoliang Xu, Muntazir Hussain, Rashid Khan, Qiang Li, Zhong Ming, Arshad Syed Muhammad Nashit
article en

Abstract

The efficient transportation of liquids by unmanned aerial vehicles (UAVs) is of utmost importance in various autonomous missions, including firefighting and field spraying. Nevertheless, liquid sloshing during transportation can lead to undesirable effects such as instability, unwanted forces, position error, and increased control effort resulting in inefficient power utilization and payload constraints. To mitigate the effects of Chlorpyrifos (pesticide) sloshing, a Lagrangianbased dynamic model of UAV and resulting slosh was developed. Using SMD analogy, sloshing and the dynamic equation of the quadcopter was modeled based on the geometry of the liquid container. An effective classical control algorithm for a liquid carrier quadcopter is presented which has been extensively investigated, validated, and compared. Simulations based on Coppelia V-rep are also presented to investigate the real time implementation of the proposed system. The results demonstrate a decrease in chlorpyrifos slosh amplitude and intuitively, a reduction in the control effort. These findings have significant implications for improving the quality of quadcopter control in various real-world applications

Southern University of Science and Technology (CN), Nanjing University of Posts and Telecommunications (CN), Shenzhen Technology University (CN)
Openalex Percentile: Top 61%
UAV Applications and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Performance Evaluation of Flight Control Strategies for a Pesticide-Carrying Unmanned Aerial Vehicle — Xiangdong Meng, Haoliang Xu, et al. · (2025) | TGRS Research Map | TGRS