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The purpose of this study is to design and verify a fuzzy logic controller for a Quadrotor,which is a nonlinear system due to its mathematical model, in real time experimental setup. In this sense performances of the fuzzy controllers were compared with the performances of PID controllers that were designed for the same Quadrotor. Controllers were verified and their performances were augmented in an experimental setup that facilitates to set parameters in real time. When nonlinear dynamics of system due to mathematical model are increasing, designed fuzzy controller trajectory pursuit and robustness performance is getting better than PID controller's performance. When the improvement in microprocessor technology is considered, fuzzy logic controller, which do not require dense mathematical operations in design process, design and verification for the control of nonlinear dynamic systems is very simple and fast. [ABSTRACT FROM AUTHOR]

In this study, a neural network assisted real-time controller has been designed for highly nonlinear quadrotor orientation control. As controlled dynamic system, a highly nonlinear quadrotor model were used in this study. The controller has been designed with neural networks for Quadrotor attitude and trajectory control, and this controller's performance was compared against the classical PID controller's performance. These controllers for dynamic systems performance evaluations were made with the help of real-time experimental setup. Attitude and trajectory controls have done for designed controllers performance evaluation. Neural network performance was compared against the classical PID controller which was designed in the same experimental setup. Designed controllers robustness was tested with pulse inputs. We observed that neural network assisted controller was more succesful than PID controller in more complicated nonlinear dynamic systems, both in attitude and trajectory control performance. We comment that with today's microcontroller technology, neural networks are faster and more simple for designing controllers for highly nonlinear dynamic systems. [ABSTRACT FROM AUTHOR]

This study includes altitude stabilization, hovering control and attitude control of quadrotor. Classically PD controller derived and applied to this system. Inverse dynamic control, feedback linearization control and sliding mode control methods have used to derive as nonlinear controllers. Linear and nonlinear control techniques applied to mathematical model as simulation and applied to quadrotor platform for experimental results. Derived control methods have been performed using computer simulations and compared the results according to this study objectives. [ABSTRACT FROM AUTHOR]