Adaptive Flight Path Control of Airborne Wind Energy Systems

Tarek N. Dief, Uwe Fechner, Roland Schmehl, Shigeo Yoshida and Mostafa A. Rushdi
Additional contact information
Tarek N. Dief: Research Institute for Applied Mechanics, Kyushu University, 6-1 Kasugakoen, Kasuga, Fukuoka 816-8580, Japan
Uwe Fechner: Aenarete–Wind Drones, 2522 DT The Hague, The Netherlands
Roland Schmehl: Faculty of Aerospace Engineering, Delft University of Technology, 2629 HS Delft, The Netherlands
Shigeo Yoshida: Research Institute for Applied Mechanics, Kyushu University, 6-1 Kasugakoen, Kasuga, Fukuoka 816-8580, Japan
Mostafa A. Rushdi: Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, 6-1 Kasugakoen, Kasuga, Fukuoka 816-8580, Japan

Energies, 2020, vol. 13, issue 3, 1-29

Abstract: In this paper, we applied a system identification algorithm and an adaptive controller to a simple kite system model to simulate crosswind flight maneuvers for airborne wind energy harvesting. The purpose of the system identification algorithm was to handle uncertainties related to a fluctuating wind speed and shape deformations of the tethered membrane wing. Using a pole placement controller, we determined the required locations of the closed-loop poles and enforced them by adapting the control gains in real time. We compared the path-following performance of the proposed approach with a classical proportional-integral-derivative (PID) controller using the same system model. The capability of the system identification algorithm to recognize sudden changes in the dynamic model or the wind conditions, and the ability of the controller to stabilize the system in the presence of such changes were confirmed. Furthermore, the system identification algorithm was used to determine the parameters of a kite with variable-length tether on the basis of data that were recorded during a physical flight test of a 20 kW kite power system. The system identification algorithm was executed in real time, and significant changes were observed in the parameters of the dynamic model, which strongly affect the resulting response.

Keywords: airborne wind energy; kite power system; system identification; adaptive algorithms; pole placement (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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