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With the developments in power electronics and microprocessor technology, it is considered that the application areas of Electronic Power Transformers (EPTs), which are expected to replace classical power transformers in the near future, will increase. One of the most important capabilities of EPTs is the ability to perform reactive power compensation without the need for additional filter elements. In addition, EPTs can be highly robust to disturbances in grid with appropriate design and control algorithms. In this study, a threephase EGT structure consisting of input, isolation and output stages is developed in the laboratory. With EPT structure, the disturbances in the grid can be compensated in the input stage of EPT. For this reason, three phase Pulse Width Modulation (PWM) based rectifier structure is preferred in the input stage of EPT. Type- 2 Neuro-Fuzzy Controller (T2NFC) is proposed instead of the classical PI or PID controller to control this rectifier structure. The proposed controller structure is used to control both the DC link voltage and the dqaxis currents of the PWM based rectifier. Furthermore, it is aimed to improve the performance of EPT against disturbances by the proposed controller structure. The control algorithms developed for the input and output stages of EPT are provided with the dSPACE DS1104 controller card. In order to evaluate the voltage sag and swell, harmonic and reactive power compensation performances of EPT, real-time operating conditions are prepared and experimental results are obtained. [ABSTRACT FROM AUTHOR]

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]