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Effects of the Coupling between the Orbital Angular Momentum and the Temporal Degrees of Freedom in the Most Intense Ring of Ultrafast Vortices

In-flight Wind Field Identification and Prediction of Parafoil Systems

College of Electrical and Electronic Engineering, Anhui Science and Technology University, Bengbu 233030, China
Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
College of Engineering, Peking University, Beijing 100871, China
University of Applied Sciences Upper Austria, Campus Steyr, Wehrgrabengasse 1, 4040 Steyr, Austria
College of Artificial Intelligence, Nankai University, Tianjin 300071, China
Predictive Society and Data Analytics Lab, Faculty of Information Technology and Communication Sciences, Tampere University, 33100 Tampere, Finland
Institute of Biosciences and Medical Technology, 33520 Tampere, Finland
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(6), 1958;
Received: 28 December 2019 / Revised: 7 March 2020 / Accepted: 10 March 2020 / Published: 12 March 2020
(This article belongs to the Special Issue Intelligent Control and Robotics)
The wind field is an essential factor that affects accurate homing and flare landing of parafoil systems. In order to obtain the ambient wind field during the descent of a parafoil system, a combination method of in-flight wind field identification and prediction is proposed. First, a wind identification method only using global position system information is derived based on the flight dynamics of parafoil systems. Then a wind field prediction model is constructed using the atmospheric dynamics, and the low-altitude wind field is predicted based on the identified wind field of high-altitude. Finally, simulations of wind field identification and prediction are conducted. The results demonstrate that the proposed method can identify the wind fields precisely and also predict the wind fields reasonably. This method can potentially be applied in practical parafoil systems to provide wind field information for homing tasks. View Full-Text
Keywords: wind field; identification; prediction; parafoil system; autonomous homing wind field; identification; prediction; parafoil system; autonomous homing
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MDPI and ACS Style

Gao, H.; Tao, J.; Dehmer, M.; Emmert-Streib, F.; Sun, Q.; Chen, Z.; Xie, G.; Zhou, Q. In-flight Wind Field Identification and Prediction of Parafoil Systems. Appl. Sci. 2020, 10, 1958.

AMA Style

Gao H, Tao J, Dehmer M, Emmert-Streib F, Sun Q, Chen Z, Xie G, Zhou Q. In-flight Wind Field Identification and Prediction of Parafoil Systems. Applied Sciences. 2020; 10(6):1958.

Chicago/Turabian Style

Gao, Haitao, Jin Tao, Matthias Dehmer, Frank Emmert-Streib, Qinglin Sun, Zengqiang Chen, Guangming Xie, and Quan Zhou. 2020. "In-flight Wind Field Identification and Prediction of Parafoil Systems" Applied Sciences 10, no. 6: 1958.

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