Özet:

In this study, the trajectory tracking problem of a rotary wing unmanned aerial vehicle has been addressed by the use of type-2 neuro-fuzzy controllers. In order to determine the effectiveness of the developed control system, simulation and experimental studies have been performed for two different trajectories. The movement of the quadrotor in each direction has been controlled by a separate controller, and the difference between the actual and target positions for the relevant axis during the trajectory tracking along with the time derivative of this value has been fed to the controllers as the input signals. In order to better evaluate the results obtained, experimental and simulation studies for the same trajectories have been repeated with proportional-integral-derivative (PID) controllers and the responses of the controllers have been compared. Real-time experimental studies have been carried out indoors in a controlled environment with the Ar.Drone 2.0 produced by Parrot company. Especially the results recorded in the real-time experiments indicate that the proposed type-2 controllers with sliding mode control theory-based learning algorithm provide less steady-state error and more robust system response.

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