Cascade model predictive control for enhancing UAV quadcopter stability and energy efficiency in wind turbulent mangrove forest environment

Unmanned aerial vehicle (UAV) modelling and control, particularly in quadrotors with high position-orientation coupling, present significant challenges for practical applications, such as environmental monitoring missions in windy mangrove forests. Conventional control strategies like the PID contro...

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Main Authors: Mustapha Amine Sadi, Annisa Jamali, Abang Mohammad Nizam bin Abang Kamaruddin, Vivien Yeo Shu Jun
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:e-Prime: Advances in Electrical Engineering, Electronics and Energy
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2772671124004169
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author Mustapha Amine Sadi
Annisa Jamali
Abang Mohammad Nizam bin Abang Kamaruddin
Vivien Yeo Shu Jun
author_facet Mustapha Amine Sadi
Annisa Jamali
Abang Mohammad Nizam bin Abang Kamaruddin
Vivien Yeo Shu Jun
author_sort Mustapha Amine Sadi
collection DOAJ
description Unmanned aerial vehicle (UAV) modelling and control, particularly in quadrotors with high position-orientation coupling, present significant challenges for practical applications, such as environmental monitoring missions in windy mangrove forests. Conventional control strategies like the PID controller, often employed in simulations due to their simplicity, often underperform in real-world scenarios due to their linear assumptions. This research proposes a novel hierarchical cascaded model predictive control system for altitude, attitude, and battery efficiency for quadrotor in mangrove area. This control system addresses computational complexity by decomposing the overall MPC strategy into two distinct schemes, one for translational displacements and another for rotational movements, enhancing the UAV's resilience to wind turbulence, a significant disturbance factor in mangrove environments. Rigorous simulation and experiment test flight involving complex trajectory tracking and windy conditions demonstrate the proposed controller's superior performance compared to conventional PID controller, particularly in terms of stability, disturbance rejection, underscoring its potential for UAV applications in challenging environments.
format Article
id doaj-art-15fc649acacf4d47b30dd6b96f0e82bb
institution Kabale University
issn 2772-6711
language English
publishDate 2024-12-01
publisher Elsevier
record_format Article
series e-Prime: Advances in Electrical Engineering, Electronics and Energy
spelling doaj-art-15fc649acacf4d47b30dd6b96f0e82bb2024-12-16T05:38:59ZengElseviere-Prime: Advances in Electrical Engineering, Electronics and Energy2772-67112024-12-0110100836Cascade model predictive control for enhancing UAV quadcopter stability and energy efficiency in wind turbulent mangrove forest environmentMustapha Amine Sadi0Annisa Jamali1Abang Mohammad Nizam bin Abang Kamaruddin2Vivien Yeo Shu Jun3Department of Mechanical Engineering, Universiti Malaysia Sarawak, MalaysiaDepartment of Mechanical Engineering, Universiti Malaysia Sarawak, Malaysia; Corresponding author.Department of Mechanical Engineering, Universiti Malaysia Sarawak, MalaysiaMangrove and Dolphin Conservation, WWF-Malaysia, Sarawak, MalaysiaUnmanned aerial vehicle (UAV) modelling and control, particularly in quadrotors with high position-orientation coupling, present significant challenges for practical applications, such as environmental monitoring missions in windy mangrove forests. Conventional control strategies like the PID controller, often employed in simulations due to their simplicity, often underperform in real-world scenarios due to their linear assumptions. This research proposes a novel hierarchical cascaded model predictive control system for altitude, attitude, and battery efficiency for quadrotor in mangrove area. This control system addresses computational complexity by decomposing the overall MPC strategy into two distinct schemes, one for translational displacements and another for rotational movements, enhancing the UAV's resilience to wind turbulence, a significant disturbance factor in mangrove environments. Rigorous simulation and experiment test flight involving complex trajectory tracking and windy conditions demonstrate the proposed controller's superior performance compared to conventional PID controller, particularly in terms of stability, disturbance rejection, underscoring its potential for UAV applications in challenging environments.http://www.sciencedirect.com/science/article/pii/S2772671124004169UAVCascade MPCPID ControllerControl designMangrove ForestWind Turbulence
spellingShingle Mustapha Amine Sadi
Annisa Jamali
Abang Mohammad Nizam bin Abang Kamaruddin
Vivien Yeo Shu Jun
Cascade model predictive control for enhancing UAV quadcopter stability and energy efficiency in wind turbulent mangrove forest environment
e-Prime: Advances in Electrical Engineering, Electronics and Energy
UAV
Cascade MPC
PID Controller
Control design
Mangrove Forest
Wind Turbulence
title Cascade model predictive control for enhancing UAV quadcopter stability and energy efficiency in wind turbulent mangrove forest environment
title_full Cascade model predictive control for enhancing UAV quadcopter stability and energy efficiency in wind turbulent mangrove forest environment
title_fullStr Cascade model predictive control for enhancing UAV quadcopter stability and energy efficiency in wind turbulent mangrove forest environment
title_full_unstemmed Cascade model predictive control for enhancing UAV quadcopter stability and energy efficiency in wind turbulent mangrove forest environment
title_short Cascade model predictive control for enhancing UAV quadcopter stability and energy efficiency in wind turbulent mangrove forest environment
title_sort cascade model predictive control for enhancing uav quadcopter stability and energy efficiency in wind turbulent mangrove forest environment
topic UAV
Cascade MPC
PID Controller
Control design
Mangrove Forest
Wind Turbulence
url http://www.sciencedirect.com/science/article/pii/S2772671124004169
work_keys_str_mv AT mustaphaaminesadi cascademodelpredictivecontrolforenhancinguavquadcopterstabilityandenergyefficiencyinwindturbulentmangroveforestenvironment
AT annisajamali cascademodelpredictivecontrolforenhancinguavquadcopterstabilityandenergyefficiencyinwindturbulentmangroveforestenvironment
AT abangmohammadnizambinabangkamaruddin cascademodelpredictivecontrolforenhancinguavquadcopterstabilityandenergyefficiencyinwindturbulentmangroveforestenvironment
AT vivienyeoshujun cascademodelpredictivecontrolforenhancinguavquadcopterstabilityandenergyefficiencyinwindturbulentmangroveforestenvironment