Wind disturbance compensated path-following control for fixed-wing UAVs in arbitrarily strong winds

LU, Hao; GAO, Lan; YAN, Yunda; HOU, Mingzhe; WANG, Chenliang

doi:10.1016/j.cja.2023.09.020

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2024

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Cited by 2 publications

References 33 publications

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Fuzzy Flight Control for Small Fixed-Wing UAV Rolling Takeoff in Presence of Strong Disturbance

Wang,

Liu,

Shui

et al. 2024

2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC)

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Fuzzy Flight Control for Small Fixed-Wing UAV Rolling Takeoff in Presence of Strong Disturbance

Wang,

Liu,

Shui

et al. 2024

2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC)

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Optimization-Assisted Filter for Flow Angle Estimation of SUAV Without Adequate Measurement

Wang,

Li,

Liu

et al. 2024

Drones

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The accurate estimation of flow angles is crucial for enhancing flight performance and aircraft safety. Flow angles of fixed-wing small unmanned aerial vehicles (SUAVs) are more vulnerable due to their low airspeed. Current flow angle measurement devices have not been widely implemented in SUAVs due to their substantial cost and size constraints. Moreover, there are no general estimation methods suitable for SUAVs based on their rudimentary sensor suite. This study presents a generalized optimization-assisted filter estimation (OAFE) method for estimating the relative velocity and flow angles of fixed-wing SUAVs based on a standard sensor suite. This OAFE method mainly consists of a cubature Kalman filter and an optimizer. The filter serves as the main loop with which to generate flow angles in real time by fusing the acceleration, angular rate, attitude, and airspeed. Without flow angle measurements, the optimizer generates approximate aerodynamic derivatives, which serve as pseudo-measurements with which to refine the performance of the filter. The results demonstrate that the estimated angle of attack and side slip angle displayed root mean square errors of around 0.11° and 0.24° in the simulation. The feasibility was also verified in field tests. The OAFE method does not require flow angle measurements, the prior acquisition of aerodynamic parameters, or model training, making it suitable for quick deployment on different SUAVs.

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Wind disturbance compensated path-following control for fixed-wing UAVs in arbitrarily strong winds

Cited by 2 publications

References 33 publications

Fuzzy Flight Control for Small Fixed-Wing UAV Rolling Takeoff in Presence of Strong Disturbance

Fuzzy Flight Control for Small Fixed-Wing UAV Rolling Takeoff in Presence of Strong Disturbance

Optimization-Assisted Filter for Flow Angle Estimation of SUAV Without Adequate Measurement

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