Modeling of Probe-Drogue Docking Success Probability for UAV Autonomous Refuelling
|Xiangmin Wang1 , Jun Wang2|
1 School of Automation, Nanjing University of Science and Technology, Nanjing, China.
2 2011 Collaborative Innovation Center, Nanjing University of Science and Technology, Nanjing, China.
Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-6 , Page no. 1-6, Jun-2018
Online published on Jun 30, 2018
Copyright © Xiangmin Wang, Jun Wang . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Xiangmin Wang, Jun Wang, “Modeling of Probe-Drogue Docking Success Probability for UAV Autonomous Refuelling”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1-6, 2018.
MLA Style Citation: Xiangmin Wang, Jun Wang "Modeling of Probe-Drogue Docking Success Probability for UAV Autonomous Refuelling." International Journal of Computer Sciences and Engineering 6.6 (2018): 1-6.
APA Style Citation: Xiangmin Wang, Jun Wang, (2018). Modeling of Probe-Drogue Docking Success Probability for UAV Autonomous Refuelling. International Journal of Computer Sciences and Engineering, 6(6), 1-6.
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|Docking process of UAV Autonomous Refueling is a critical issue during the docking phase of autonomous aerial refueling (AAR), and the successful docking between the probe and drogue need higher probability for an aerial refueling system. To cope with this issue, a novel and effective model based on the theory of stochastic process crossing target area is proposed. In order to ensure its accurate and easy application, according to prior information and assumptions for the movements of the probe related to the drogue, the probe-drogue docking success probability is converted to the probability of the probe located in the circle area of drogue. The temporal and spatial characteristics of the pointing error have been considered which makes the model of the docking success probability more accord with the actual situation. simulations were conducted to demonstrate the effectiveness of the proposed method. This model provides theoretical support for the design and verification of AAR’s control system.|
|Key-Words / Index Term :|
|Autonomous aerial refueling, UAV, stochastic process, docking success probability|
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