A neural network based landing method for an unmanned aerial vehicle with soft landing gears
Luo, Cai and Zhao, Weikang and Du, Zhenpeng and Yu, Leijian (2019) A neural network based landing method for an unmanned aerial vehicle with soft landing gears. Applied Sciences, 9 (15). 2976. ISSN 2076-3417 (https://doi.org/10.3390/app9152976)
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Abstract
This paper presents the design, implementation, and testing of a soft landing gear together with a neural network-based control method for replicating avian landing behavior on non-flat surfaces. With full consideration of unmanned aerial vehicles and landing gear requirements, a quadrotor helicopter, comprised of one flying unit and one landing assistance unit, is employed. Considering the touchdown speed and posture, a novel design of a soft mechanism for non-flat surfaces is proposed, in order to absorb the remaining landing impact. The framework of the control strategy is designed based on a derived dynamic model. A neural network-based backstepping controller is applied to achieve the desired trajectory. The simulation and outdoor testing results attest to the effectiveness and reliability of the proposed control method.
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Item type: Article ID code: 69075 Dates: DateEvent25 July 2019Published22 July 2019AcceptedSubjects: Technology > Motor vehicles. Aeronautics. Astronautics Department: Faculty of Engineering > Design, Manufacture and Engineering Management Depositing user: Pure Administrator Date deposited: 26 Jul 2019 13:56 Last modified: 19 Nov 2024 01:13 URI: https://strathprints.strath.ac.uk/id/eprint/69075