Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area : A Hybrid PID-Grey Wolf Optimizer Control Approach

Quadrotor Unmanned Aerial Vehicles (UAVs) offer versatile platforms for various applications including disaster response and environmental monitoring. However, their effective utilization in wind-disturbed environments such as mangroves poses unique challenges due to complex wind turbulence, impacti...

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Main Authors: Mustapha Amine, Sadi, Annisa, Jamali, Abang Mohammad Nizam, Abang Kamaruddin
Format: Proceeding
Language:English
Published: 2024
Subjects:
Online Access:http://ir.unimas.my/id/eprint/44008/5/Enhancing.pdf
http://ir.unimas.my/id/eprint/44008/
https://ieeexplore.ieee.org/document/10373472
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spelling my.unimas.ir.440082024-01-05T07:30:32Z http://ir.unimas.my/id/eprint/44008/ Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area : A Hybrid PID-Grey Wolf Optimizer Control Approach Mustapha Amine, Sadi Annisa, Jamali Abang Mohammad Nizam, Abang Kamaruddin TA Engineering (General). Civil engineering (General) Quadrotor Unmanned Aerial Vehicles (UAVs) offer versatile platforms for various applications including disaster response and environmental monitoring. However, their effective utilization in wind-disturbed environments such as mangroves poses unique challenges due to complex wind turbulence, impacting flight stability and navigation accuracy. Traditional control systems often fall short of ensuring robust and precise control in such conditions. This study presents a hybrid control approach combining a Proportional-Integral-Derivative (PID) control system with the Grey Wolf Optimizer (GWO) for enhanced UAV performance in challenging conditions. The PID controller, known for its effectiveness in industrial control systems, provides a control loop feedback mechanism to minimize flight errors, while the GWO, a bio-inspired optimization algorithm, automates the process of tuning PID parameters. Preliminary results show that this hybrid PID-GWO system significantly improves the UAV's robustness and adaptability under varying wind conditions, outperforming the standalone PID controller. This research illuminates a new direction for optimizing UAV performance in wind-disturbed environments and suggests further exploration of bio-inspired optimization techniques in UAV control systems. 2024-01-03 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/44008/5/Enhancing.pdf Mustapha Amine, Sadi and Annisa, Jamali and Abang Mohammad Nizam, Abang Kamaruddin (2024) Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area : A Hybrid PID-Grey Wolf Optimizer Control Approach. In: 9th IEEE International Conference On Smart Instrumentation, Measurement and Application, 17-18 Oct 2023, Tamu Hotel, KL. https://ieeexplore.ieee.org/document/10373472
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Mustapha Amine, Sadi
Annisa, Jamali
Abang Mohammad Nizam, Abang Kamaruddin
Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area : A Hybrid PID-Grey Wolf Optimizer Control Approach
description Quadrotor Unmanned Aerial Vehicles (UAVs) offer versatile platforms for various applications including disaster response and environmental monitoring. However, their effective utilization in wind-disturbed environments such as mangroves poses unique challenges due to complex wind turbulence, impacting flight stability and navigation accuracy. Traditional control systems often fall short of ensuring robust and precise control in such conditions. This study presents a hybrid control approach combining a Proportional-Integral-Derivative (PID) control system with the Grey Wolf Optimizer (GWO) for enhanced UAV performance in challenging conditions. The PID controller, known for its effectiveness in industrial control systems, provides a control loop feedback mechanism to minimize flight errors, while the GWO, a bio-inspired optimization algorithm, automates the process of tuning PID parameters. Preliminary results show that this hybrid PID-GWO system significantly improves the UAV's robustness and adaptability under varying wind conditions, outperforming the standalone PID controller. This research illuminates a new direction for optimizing UAV performance in wind-disturbed environments and suggests further exploration of bio-inspired optimization techniques in UAV control systems.
format Proceeding
author Mustapha Amine, Sadi
Annisa, Jamali
Abang Mohammad Nizam, Abang Kamaruddin
author_facet Mustapha Amine, Sadi
Annisa, Jamali
Abang Mohammad Nizam, Abang Kamaruddin
author_sort Mustapha Amine, Sadi
title Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area : A Hybrid PID-Grey Wolf Optimizer Control Approach
title_short Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area : A Hybrid PID-Grey Wolf Optimizer Control Approach
title_full Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area : A Hybrid PID-Grey Wolf Optimizer Control Approach
title_fullStr Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area : A Hybrid PID-Grey Wolf Optimizer Control Approach
title_full_unstemmed Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area : A Hybrid PID-Grey Wolf Optimizer Control Approach
title_sort enhancing quadrotor uav efficiency amidst turbulent winds in mangrove area : a hybrid pid-grey wolf optimizer control approach
publishDate 2024
url http://ir.unimas.my/id/eprint/44008/5/Enhancing.pdf
http://ir.unimas.my/id/eprint/44008/
https://ieeexplore.ieee.org/document/10373472
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score 13.160551