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System Identification of a 6 m2 Kite Power System in Fixed-Tether Length Operation

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The traction force of a kite system can be utilized for extracting energy from high-altitude wind. This paper discusses a system identification algorithm derived to obtain real-time governing equations for the kite system based on real-flight data, obtained from a 6 m2 kite power system developed in Kyushu University as an airborne wind energy project. The paper presents the system set-up, the design, the experimental results, a system identification algorithm, and the parameters identified for the kite used. The current stage of the project considers the kite application as a fixed-tether length system with a ground kite control unit. The control strategy is designed to work as a hardware-in the-loop to keep receiving the data and controlling the kite in real time. The experimental tests employed are divided into four distinct ones, and the data of the kite’s attitude, position, and tension forces are recorded. The tension forces resulted from these tests are presented for different wind speeds and flight modes. Ultimately, a novel system identification algorithm that evaluates the correlation between the tension force and the kite’s rolling angle over the four tests is applied, thereby enabling to study the kite behavior as a preliminary step for the achievement of autonomous flight.
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Airborne Wind Energy; Kite; System Identification

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R. Schmehl, Airborne Wind Energy: Advances in Technology Development and Research, first ed. (Springer, Singapore, 2018).

U. Ahrens, M. Diehl, and R. Schmehl, Airborne Wind Energy, first ed. (Springer Science & Business Media, Berlin, 2013).

A. Cherubini, et al. Airborne Wind Energy Systems: A Review of the Technologies, Renewable and Sustainable Energy Reviews, 51 (2015), 1461-1476.

A. K. S. Mendonça, et al., Comparing Patent and Scientific Literature in Airborne Wind Energy, Sustainability 9, 915 (2017), 1-22.

M. Rushdi, S. Yoshida, and T. N. Dief, Simulation of a Tether of a Kite Power System Using a Lumped Mass Model, IEICES Proceedings, 42-47 (2018).

M. Rushdi, et al., Simulation of the Transition Phase for an Optimally-Controlled Tethered VTOL Rigid Aircraft for Airborne Wind Energy Generation, AIAA Scitech 2020 Forum. (2020), 1243.

M. N., Noom, Theoretical analysis of mechanical power generation by pumping cycle kite power systems, Ms.c. Dissertation, Dept. Wind Energy, TU Delft, Delft, (2013).

Kite Energy Company, [Accessed February 2020].

KiteGen Company, [Accessed February 2020].

Kitepower Company, [Accessed February 2020].

T. N. Dief, et al., Hardware-in-the-Loop (HIL) and Experimental Findings for the 7 kW Pumping Kite Power System, AIAA Scitech 2020 Forum (2020), 1244.

B. L. Ho and R. E. Kálmán. Effective construction of linear state-variable models from input/output functions. at-Automatisierungstechnik 14.1-12 (1966): 545-548.

K.-J. Åström and B. Torsten. Numerical identification of linear dynamic systems from normal operating records. IFAC Proceedings Volumes 2,2 (1965), 96-111.

M. Deistler. System identification and time series analysis: Past, present, and future. Stochastic Theory and Control. Springer, Berlin, Heidelberg, (2002), 97-109.

L. A. H. Petersen, et al., Modeling and system identification of an unconventional bioreactor used for single cell protein production. Chemical Engineering Journal 390 (2020): 124438.

K. K. Wallinger, and M. Huemer. Volatility Clustering in Medical Ultrasound Imaging and System Identification Based Deconvolution. 2019 IEEE International Ultrasonics Symposium (IUS). (2019), 1459-1462.

R. T. Torres, and F. Sergii. Brushless Direct Current Propulsion System Identification. Integrated Computer Technologies in Mechanical Engineering. Springer, Cham, (2020), 105-113.

M. S. Gandhi, et al. Practical system identification for small VTOL unmanned aerial vehicle. AIAA Scitech 2019 forum. (2019), 1982.

OQatamin, R., Mohamed, O., Abu Elhaija, W., Prediction of Power Output of Wind Turbines Using System Identification Techniques, (2020) International Review on Modelling and Simulations (IREMOS), 13 (1), pp. 43-51.

T. Weber, et al. Machine Learning based System Identification Tool for data-based Energy and Resource Modeling and Simulation. Procedia CIRP 80 (2019), 683-688.

G. C. Clifford, and R. L. Payne. Dynamic System Identification. Experiment Design and Data Analysis, (Academic Press, New York, 1977).

T. N. Dief, et al., Adaptive Flight Path Control of Airborne Wind Energy Systems, Energies, 13, 667 (2020), 1-28.

T. N. Dief, et al., System Identification, Fuzzy Control and Simulation of a Kite Power System with Fixed Tether Length. Wind Energy Science 3, 1 (2018), 275-291.

G. Licitra, et al., System Identification of a Rigid Wing Airborne Wind Energy System, arXiv preprint arXiv:1711.10010 (2017).

G. Licitra, et al., Performance Assessment of a Rigid Wing Airborne Wind Energy Pumping System, Energy 173 (2019), 569-585.

Dief, T., Kamra, M., Yoshida, S., Modeling, System Identification and PID-A Controller for Tethered Unmanned Quad-Rotor Helicopter, (2017) International Review of Aerospace Engineering (IREASE), 10 (4), pp. 215-223.
K. Dutton, The Art of Control Engineering. (Addison-Wesley Longman Publishing Co., Harlow, (1997).

Solo, V. The convergence of AML. IEEE Transactions on Automatic Control, 24, 6, (1979), 958-962.

Lockwood, S., Haase, F., & Ford, D. G. Active vibration control of machine tool structures-Part 1: DSP algorithms. WIT Transactions on Engineering Sciences, 44. (2003), 441-450.

Khaddaj Mallat, N., Zia, M., Mirza, N., Comparison of RLS and LMS Algorithms for Interference Cancelation in a Fixed Point to Point Microwave Link, (2017) International Journal on Communications Antenna and Propagation (IRECAP), 7 (5), pp. 448-456.

Celeita Rodriguez, D., Ramos, G., Sakis Meliopoulos, A., Transmission Line Protective Relay Based on Recursive Least-Square Filters and Weights Analysis, (2018) International Review on Modelling and Simulations (IREMOS), 11 (5), pp. 277-287.

Alkurawy, L., Saleh, M., Fatah, I., Saleh, A., Modeling and Identification of Human Heart System, (2019) International Journal on Engineering Applications (IREA), 7 (4), pp. 130-136.


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