Design, Modeling, and Control of a Fully Actuated Multirotor with Multidirectional Thrusts

This paper introduces a novel multirotor Unmanned Aerial Vehicles (UAV) configuration with inclinable rotors, extendable arms, and a spatial arrangement, categorized under a new classification system based on articulation and rotor dispersion. A comprehensive nonlinear mathematical model is developed to account for asymmetry, rotor placement, and dynamic behavior. The model is validated through MATLAB simulations across multiple scenarios, demonstrating precise complex trajectory tracking. The proposed PID control parameters were optimized using Particle Swarm Optimization (PSO), achieving significant improvements in control effort and energy efficiency. Results highlight the UAV’s adaptability and performance, providing a foundation for future research on robust control methods to handle real-world disturbances.

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Publication Details

Journal
Unmanned Systems
Published
2025-04-24
DOI
https://doi.org/10.1142/s2301385026500391
Primary Topic
Aerospace Engineering and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Design, Modeling, and Control of a Fully Actuated Multirotor with Multidirectional Thrusts

Saddam Hocine Derrouaoui, Yasser Bouzid, Mariyam Jameelah Ghazali, Mahmoud Belhocine
Unmanned Systems
Aerospace Engineering and Control Systems
article

Design, Modeling, and Control of a Fully Actuated Multirotor with Multidirectional Thrusts

Saddam Hocine Derrouaoui, Yasser Bouzid, Mariyam Jameelah Ghazali, Mahmoud Belhocine
article en

Abstract

This paper introduces a novel multirotor Unmanned Aerial Vehicles (UAV) configuration with inclinable rotors, extendable arms, and a spatial arrangement, categorized under a new classification system based on articulation and rotor dispersion. A comprehensive nonlinear mathematical model is developed to account for asymmetry, rotor placement, and dynamic behavior. The model is validated through MATLAB simulations across multiple scenarios, demonstrating precise complex trajectory tracking. The proposed PID control parameters were optimized using Particle Swarm Optimization (PSO), achieving significant improvements in control effort and energy efficiency. Results highlight the UAV’s adaptability and performance, providing a foundation for future research on robust control methods to handle real-world disturbances.

Unmanned Systems
Polytechnic School of Algiers (DZ), Centre de Développement des Technologies Avancées (DZ)
Affordable and clean energy
Openalex Percentile: Top 89%
Aerospace Engineering and Control Systems
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