Dual-layer optimization-based control allocation for a fixed-wing UAV

Yan, Yunda; Liu, Cunjia; Oh, Hyondong; Chen, Wenhua

doi:10.1016/j.ast.2021.107184

Cited by 4 publications

(1 citation statement)

References 40 publications

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“…An ultrasonic wind sensor was mounted on the drone to measure the real-time wind parameters that can be further utilized as feedback to the controller [27]. Alternatively, wind disturbances to the UAV can be estimated via the nonlinear Disturbance Observer (DOB) which can then be compensated by Disturbance Observer-Based Control (DOBC) designs [28][29][30]. Whereas, there are limited studies for vision-based landing systems, focusing on scenarios when the vision is lost during the landing due to wind disturbances which results in no feedback signal to the controller.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based UAV Landing with Guaranteed Reliability in Adverse Environment

Jiang

Pugh

et al. 2023

Electronics

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Safe and accurate landing is crucial for Unmanned Aerial Vehicles (UAVs). However, it is a challenging task, especially when the altitude of the landing target is different from the ground and when the UAV is working in adverse environments, such as coasts where winds are usually strong and changing rapidly. UAVs controlled by traditional landing algorithms are unable to deal with sudden large disturbances, such as gusts, during the landing process. In this paper, a reliable vision-based landing strategy is proposed for UAV autonomous landing on a multi-level platform mounted on an Unmanned Ground Vehicle (UGV). With the proposed landing strategy, visual detection can be retrieved even with strong gusts and the UAV is able to achieve robust landing accuracy in a challenging platform with complex ground effects. The effectiveness of the landing algorithm is verified through real-world flight tests. Experimental results in farm fields demonstrate the proposed method’s accuracy and robustness to external disturbances (e.g., wind gusts).

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