A Review of Modeling and Control Techniques for Unmanned Aerial Vehicles
ABSTRACT Unmanned Aerial Vehicles (UAVs), particularly quadcopters, have found growing applications across diverse sectors such as surveillance, precision agriculture, and transport. However, their nonlinear dynamics, underactuated systems, and sensitivity to disturbances present persistent challeng...
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | Engineering Reports |
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| Online Access: | https://doi.org/10.1002/eng2.70215 |
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| _version_ | 1850163573696757760 |
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| author | Elisabeth Andarge Gedefaw Nardos Belay Abera Chala Merga Abdissa |
| author_facet | Elisabeth Andarge Gedefaw Nardos Belay Abera Chala Merga Abdissa |
| author_sort | Elisabeth Andarge Gedefaw |
| collection | DOAJ |
| description | ABSTRACT Unmanned Aerial Vehicles (UAVs), particularly quadcopters, have found growing applications across diverse sectors such as surveillance, precision agriculture, and transport. However, their nonlinear dynamics, underactuated systems, and sensitivity to disturbances present persistent challenges in achieving robust and autonomous control. This review systematically examines advancements in UAV modeling and control techniques over the past five years. The study evaluates key modeling frameworks, Newton–Euler, Newton–Quaternion, and Geometry‐Based Stochastic Models (GBSM), and analyzes a spectrum of control strategies, including observer‐based, sliding mode, H‐infinity, model predictive, and neural network‐based controllers. Through a comparative assessment of their robustness, computational efficiency, and adaptability, the manuscript identifies critical limitations in handling uncertainties, scalability in UAV systems, and energy constraints. The findings highlight that hybrid control strategies incorporating adaptive mechanisms, learning‐based algorithms, and quaternion‐based modeling offer significant potential for enhancing autonomy and control. Therefore, this review provides a foundational roadmap for researchers and practitioners aiming to develop intelligent, efficient, and scalable UAV control systems capable of thriving in dynamic operational environments. |
| format | Article |
| id | doaj-art-1938f80058a3442f99cb7bcffeab9429 |
| institution | OA Journals |
| issn | 2577-8196 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Engineering Reports |
| spelling | doaj-art-1938f80058a3442f99cb7bcffeab94292025-08-20T02:22:14ZengWileyEngineering Reports2577-81962025-06-0176n/an/a10.1002/eng2.70215A Review of Modeling and Control Techniques for Unmanned Aerial VehiclesElisabeth Andarge Gedefaw0Nardos Belay Abera1Chala Merga Abdissa2School of Electrical and Computer Engineering Addis Ababa University Addis Ababa EthiopiaSchool of Electrical and Computer Engineering Addis Ababa University Addis Ababa EthiopiaSchool of Electrical and Computer Engineering Addis Ababa University Addis Ababa EthiopiaABSTRACT Unmanned Aerial Vehicles (UAVs), particularly quadcopters, have found growing applications across diverse sectors such as surveillance, precision agriculture, and transport. However, their nonlinear dynamics, underactuated systems, and sensitivity to disturbances present persistent challenges in achieving robust and autonomous control. This review systematically examines advancements in UAV modeling and control techniques over the past five years. The study evaluates key modeling frameworks, Newton–Euler, Newton–Quaternion, and Geometry‐Based Stochastic Models (GBSM), and analyzes a spectrum of control strategies, including observer‐based, sliding mode, H‐infinity, model predictive, and neural network‐based controllers. Through a comparative assessment of their robustness, computational efficiency, and adaptability, the manuscript identifies critical limitations in handling uncertainties, scalability in UAV systems, and energy constraints. The findings highlight that hybrid control strategies incorporating adaptive mechanisms, learning‐based algorithms, and quaternion‐based modeling offer significant potential for enhancing autonomy and control. Therefore, this review provides a foundational roadmap for researchers and practitioners aiming to develop intelligent, efficient, and scalable UAV control systems capable of thriving in dynamic operational environments.https://doi.org/10.1002/eng2.70215Newton–EulerNewton–QuaternionquadcopterUAVs |
| spellingShingle | Elisabeth Andarge Gedefaw Nardos Belay Abera Chala Merga Abdissa A Review of Modeling and Control Techniques for Unmanned Aerial Vehicles Engineering Reports Newton–Euler Newton–Quaternion quadcopter UAVs |
| title | A Review of Modeling and Control Techniques for Unmanned Aerial Vehicles |
| title_full | A Review of Modeling and Control Techniques for Unmanned Aerial Vehicles |
| title_fullStr | A Review of Modeling and Control Techniques for Unmanned Aerial Vehicles |
| title_full_unstemmed | A Review of Modeling and Control Techniques for Unmanned Aerial Vehicles |
| title_short | A Review of Modeling and Control Techniques for Unmanned Aerial Vehicles |
| title_sort | review of modeling and control techniques for unmanned aerial vehicles |
| topic | Newton–Euler Newton–Quaternion quadcopter UAVs |
| url | https://doi.org/10.1002/eng2.70215 |
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