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Research paper

Enhanced Approaches of Precision Thrust Vector Control for Aerial Vehicles: Comprehensive Modeling and Validation

Aerospace Department, Faculty of Engineering, Cairo University, Cairo, Egypt
College Arab Academy for Science, Technology & Maritime Transport, Cairo, Egypt

This paper was recommended for publication in its revised form by editorial board member, Jianan Wang.

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Abstract

The Thrust vector control (TVC) is a method for controlling the angular velocity and attitude of aerial vehicles (AV) by manipulating the thrust direction of propulsion. This technology enhances maneuverability and allows for dynamic aerobatics at low speeds and near-zero airspeeds without stalling at high angles of attack (AOA). As the aerodynamic control surfaces are ineffective for vehicles operating outside the atmosphere, TVC is a suitable technique for these applications. To design a control system for AVs utilizing TVC, an accurate mathematical model is essential to simulate flight parameters and optimize the control gains. This work presents a complete six degrees-of-freedom (6-DOF) high-fidelity simulation model of a thrust vector control aerial vehicle (TVC-AV). The nonlinear model is developed by dividing the mathematical representation into five submodules, including the geometrical model, the actuation model that was experimentally identified, and an aerodynamic model that was validated through semi-empirical techniques, computational fluid dynamics (CFD), and wind-tunnel experiments; in addition, the propulsion model’s characteristics are identified through experimentation, and the atmospheric model is based on International Standard Atmosphere (ISA) values. The integrated model was implemented in MATLAB® (Simulink) that provides a foundation for designing effective flight controllers and guidance systems.

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Unmanned Systems
Pages 415-439

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Cite this article:
Ahmed MM, ElBayoumi GM, Elbanna AE. Enhanced Approaches of Precision Thrust Vector Control for Aerial Vehicles: Comprehensive Modeling and Validation. Unmanned Systems, 2026, 14(2): 415-439. https://doi.org/10.1142/S2301385026500093

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Received: 19 September 2024
Accepted: 16 January 2025
Published: 18 March 2025
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