In wind energy research, airborne wind energy systems are one of the promising energy sources in the near future. They can extract more energy from high altitude wind currents compared to conventional wind turbines. This can be achieved with the aid of aerodynamic lift generated by a wing tethered to the ground. Significant savings in investment costs and overall system mass would be obtained since no tower is required. To solve the problems of wind speed uncertainty and kite deflections throughout the flight, system identification is required. Consequently, the kite governing equations can be accurately described. In this work, a simple model was presented for a tether with a fixed length and compared to another model for parameter estimation. In addition, for the purpose of stabilizing the system, fuzzy control was also applied. The design of the controller was based on the concept of Mamdani. Due to its robustness, fuzzy control can cover a wider range of different wind conditions compared to the classical controller. Finally, system identification was compared to the simple model at various wind speeds, which helps to tune the fuzzy control parameters.

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This work demonstrates the derivation of the equations governing the operation of a kite power system, followed by adaptive control with time-varying gains. Because the availablemathematical kite models are generally derived with aggressive assumptions,we use least square estimation as a system identification (SI) algorithm [1] to predict the kite parameters in real-time and compare between the measured and expected course angle to check the accuracy of the model as shown in the figure. The SI algorithms are chosen to minimize the computational effort per time step. Two different controllers are tested separately to stabilize the kite motion; the first controller is a fuzzy controller which is chosen due to its strength in stabilizing non-linear systems. The other controller is an adaptive pole placement controller which updates its control gains in real-time depending on the parameters generated from the SI algorithms. The SI algorithms with fuzzy and adaptive controllers are compared with the mathematical model of the fixed-tether-length kite system with PID controller at different wind conditions. The novelty of this work is to predict the governing equation of the kite in real-time. Thus, the change in kite’s size, wind speed, and tether length [2] would be updated in the mathematical model of the kite. Moreover, the governing equations resulting from the SI algorithms are used to design an adaptive controller that adapts its gains in real-time based on the change of the governing equations of the kite. @en