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

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[Formula: see text] (Simulink) that provides a foundation for designing effective flight controllers and guidance systems.

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Publication Details

Journal
Unmanned Systems
Published
2025-01-22
DOI
https://doi.org/10.1142/s2301385026500093
Citations
1
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
1.21
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article

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

Gamal El-Bayoumi, Mohamed Ahmed, Ahmed E. Elbanna
1 citations
Unmanned Systems
Adaptive Control of Nonlinear Systems
1.21
article

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

Gamal El-Bayoumi, Mohamed Ahmed, Ahmed E. Elbanna
article en
1 citations

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[Formula: see text] (Simulink) that provides a foundation for designing effective flight controllers and guidance systems.

Unmanned SystemsVol. 14(02)
Cairo University (EG), Arab Academy for Science, Technology, and Maritime Transport (EG)
Openalex Percentile: Top 25%
Adaptive Control of Nonlinear Systems
1.21
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Enhanced Approaches of Precision Thrust Vector Control for Aerial Vehicles: Comprehensive Modeling and Validation — Gamal El-Bayoumi, Mohamed Ahmed, et al. · Unmanned Systems (2025) | TGRS Research Map | TGRS