Control of Multiple-UAV Conveying Slung Load With Obstacle Avoidance

Quadrotor Unmanned Aerial Vehicles (UAVs) are generally underactuated systems and when load is attached for transportation purposes, the system complexity increases. Therefore, the need to appropriately control such systems becomes paramount as they usually navigate in cluttered environments. In thi...

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Main Authors: Abdulrahman Aliyu, Sami El Ferik
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9787541/
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author Abdulrahman Aliyu
Sami El Ferik
author_facet Abdulrahman Aliyu
Sami El Ferik
author_sort Abdulrahman Aliyu
collection DOAJ
description Quadrotor Unmanned Aerial Vehicles (UAVs) are generally underactuated systems and when load is attached for transportation purposes, the system complexity increases. Therefore, the need to appropriately control such systems becomes paramount as they usually navigate in cluttered environments. In this work, we conceptualize the problem of cooperative tracking control for a Multi-agent UAV load system (MUAVLs) whereby each UAV is divided into global position and local attitude subsystems. To ensure that formation is maintained in a desired path, Neural Network Graph-theoretic Distributed Adaptive Control (NNGDAC) is used for the position subsystem with a modified virtual force artificial potential field for obstacle avoidance. Another Adaptive Feedback Linearization (AFBL) controller is also designed for the attitude subsystem which is verified by simulation results.
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spelling doaj.art-0701d43eb3654a13a81cb21177c1bf002022-12-22T03:29:33ZengIEEEIEEE Access2169-35362022-01-0110622476225710.1109/ACCESS.2022.31799849787541Control of Multiple-UAV Conveying Slung Load With Obstacle AvoidanceAbdulrahman Aliyu0https://orcid.org/0000-0002-2101-3340Sami El Ferik1https://orcid.org/0000-0001-5648-4786Department of Control and Instrumentation Engineering, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi ArabiaDepartment of Control and Instrumentation Engineering, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi ArabiaQuadrotor Unmanned Aerial Vehicles (UAVs) are generally underactuated systems and when load is attached for transportation purposes, the system complexity increases. Therefore, the need to appropriately control such systems becomes paramount as they usually navigate in cluttered environments. In this work, we conceptualize the problem of cooperative tracking control for a Multi-agent UAV load system (MUAVLs) whereby each UAV is divided into global position and local attitude subsystems. To ensure that formation is maintained in a desired path, Neural Network Graph-theoretic Distributed Adaptive Control (NNGDAC) is used for the position subsystem with a modified virtual force artificial potential field for obstacle avoidance. Another Adaptive Feedback Linearization (AFBL) controller is also designed for the attitude subsystem which is verified by simulation results.https://ieeexplore.ieee.org/document/9787541/UAVsmulti-agent systemsintelligent controlgraph theoryload transportation
spellingShingle Abdulrahman Aliyu
Sami El Ferik
Control of Multiple-UAV Conveying Slung Load With Obstacle Avoidance
IEEE Access
UAVs
multi-agent systems
intelligent control
graph theory
load transportation
title Control of Multiple-UAV Conveying Slung Load With Obstacle Avoidance
title_full Control of Multiple-UAV Conveying Slung Load With Obstacle Avoidance
title_fullStr Control of Multiple-UAV Conveying Slung Load With Obstacle Avoidance
title_full_unstemmed Control of Multiple-UAV Conveying Slung Load With Obstacle Avoidance
title_short Control of Multiple-UAV Conveying Slung Load With Obstacle Avoidance
title_sort control of multiple uav conveying slung load with obstacle avoidance
topic UAVs
multi-agent systems
intelligent control
graph theory
load transportation
url https://ieeexplore.ieee.org/document/9787541/
work_keys_str_mv AT abdulrahmanaliyu controlofmultipleuavconveyingslungloadwithobstacleavoidance
AT samielferik controlofmultipleuavconveyingslungloadwithobstacleavoidance