Active Disturbance Rejection Flight Control and Simulation of Unmanned Quad Tilt Rotor eVTOL Based on Adaptive Neural Network

The unmanned quad tilt-rotor eVTOL (QTRV) is a variable-configuration aircraft that combines the features of vertical takeoff and landing (VTOL), hovering, and high-speed cruising, making its control system design particularly challenging. The flight dynamics of the QTRV differ significantly between the VTOL and cruise modes, and are further influenced by rotor tilt and external wind disturbances. Developing a unified, highly coupled nonlinear full-flight dynamics model facilitates flight control system design and simulation verification. To ensure stable tilt of the QTRV, a tilt corridor was established, along with the design of its tilt route and manipulation strategy. An adaptive neural network active disturbance rejection controller (ANN-ADRC) is proposed to ensure stable flight across all modes, reducing the control parameters and simplifying tuning while effectively estimating and compensating for unknown disturbances in real time. A hardware-in-the-loop (HIL) simulation system was designed for full-mode flight control simulation, and the results demonstrated the effectiveness of the proposed control method.

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Publication Details

Journal
Drones
Published
2024-10-08
DOI
https://doi.org/10.3390/drones8100560
Citations
9
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
2.95

Funders

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article

Active Disturbance Rejection Flight Control and Simulation of Unmanned Quad Tilt Rotor eVTOL Based on Adaptive Neural Network

Bohai Deng, Shengxin Yu, Jinfa Xu, Xingyu Yuan
9 citations
Drones
Adaptive Control of Nonlinear Systems
2.95
article

Active Disturbance Rejection Flight Control and Simulation of Unmanned Quad Tilt Rotor eVTOL Based on Adaptive Neural Network

Bohai Deng, Shengxin Yu, Jinfa Xu, Xingyu Yuan
article en
9 citations

Abstract

The unmanned quad tilt-rotor eVTOL (QTRV) is a variable-configuration aircraft that combines the features of vertical takeoff and landing (VTOL), hovering, and high-speed cruising, making its control system design particularly challenging. The flight dynamics of the QTRV differ significantly between the VTOL and cruise modes, and are further influenced by rotor tilt and external wind disturbances. Developing a unified, highly coupled nonlinear full-flight dynamics model facilitates flight control system design and simulation verification. To ensure stable tilt of the QTRV, a tilt corridor was established, along with the design of its tilt route and manipulation strategy. An adaptive neural network active disturbance rejection controller (ANN-ADRC) is proposed to ensure stable flight across all modes, reducing the control parameters and simplifying tuning while effectively estimating and compensating for unknown disturbances in real time. A hardware-in-the-loop (HIL) simulation system was designed for full-mode flight control simulation, and the results demonstrated the effectiveness of the proposed control method.

DronesVol. 8(10)
Nanjing University of Aeronautics and Astronautics (CN)
Priority Academic Program Development of Jiangsu Higher Education Institutions
Affordable and clean energy
Openalex Percentile: Top 8%
Adaptive Control of Nonlinear Systems
2.95
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Active Disturbance Rejection Flight Control and Simulation of Unmanned Quad Tilt Rotor eVTOL Based on Adaptive Neural Network — Bohai Deng, Shengxin Yu, et al. · Drones (2024) | TGRS Research Map | TGRS