Abstract
| Original language | English |
|---|---|
| Article number | 2976 |
| Number of pages | 16 |
| Journal | Applied Sciences |
| Volume | 9 |
| Issue number | 15 |
| DOIs | |
| Publication status | Published - 25 Jul 2019 |
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Keywords
- unmanned aerial vehicle
- neural network
- soft landing gear
- aerospace
- design
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A neural network based landing method for an unmanned aerial vehicle with soft landing gears. / Luo, Cai; Zhao, Weikang; Du, Zhenpeng; Yu, Leijian.
In: Applied Sciences, Vol. 9, No. 15, 2976, 25.07.2019.Research output: Contribution to journal › Article
TY - JOUR
T1 - A neural network based landing method for an unmanned aerial vehicle with soft landing gears
AU - Luo, Cai
AU - Zhao, Weikang
AU - Du, Zhenpeng
AU - Yu, Leijian
PY - 2019/7/25
Y1 - 2019/7/25
N2 - 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.
AB - 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.
KW - unmanned aerial vehicle
KW - neural network
KW - soft landing gear
KW - aerospace
KW - design
U2 - 10.3390/app9152976
DO - 10.3390/app9152976
M3 - Article
VL - 9
JO - Applied Sciences
JF - Applied Sciences
SN - 2076-3417
IS - 15
M1 - 2976
ER -