Ceyhun Yildiz

RBF based induction motor control with a good nonlinearity compensation

This work introduces an artificial neural network based speed control system for AC induction motors. In motor control, Radial Basis Function (RBF) network and Volt-Hertz (V/f) method have been adopted as neural controller and scalar driving tool respectively. V/Hz method has been preferred for the sake of simplicity and well-known reliability. The proposed control scheme consists of two main parts; a RBF network and a reference model unit. RBF based main controller supplies appropriate control signals to the driving unit to compensate nonlinearity of the induction motor and track the reference model output. Reference model, is very stable linear filter which is supplying set values to be imitated by induction motor. The success of the proposed control scheme has been demonstrated by experimental results; induction motor has been able to track the prescribed speed trajectory with rather small errors and good stability under properly loading conditions.

Investigation and Evaluation of wind power estimation at the Campus area of Kahramanmaraş Sutcu İmam University

This paper briefly introduces a study of the determination of possible wind power potential in Kahramanmaras, For this purpose, a wind observation mast and its measurement equipment was established at the main campus of kahramanmaras Sutcu Imam University. Wind meteorological data were collected and recorded between the dates of October 05, 2010 and April 24, 2012. The recorded data were analyzed and processed using the WAsP program. The results of these analyses are used to estimate the wind power potential in the region and select the best fitted wind turbines to the site characteristics. Suitable sites were selected according to the created wind power and energy maps.

Speed control of induction motor based on model reference adaptive control

In recent years, adaptive and intelligent control schemes have begun to take the place of conventional control methods. In this study, a model reference adaptive control (MRAC) scheme based on genetic algorithm (GA) and Fuzzy Logic (FL) has been used by the help of Vector Control type driving method based on Space Vector Pulse Width Modulation (SVPWM). In this control technique, the conventional PI controller and the proposed control strategy has been applied to induction motor in real conditions by using an appropriate digital signal processor and peripheral units. As digital processor, DSPIC 30F6010 which is produced by Microchip Co. has been used. Experimental studies have been implemented for both of the control techniques under the same conditions. The results obtained from conventional PI controller and the proposed control strategy have been analysed and compared.

Power Quality Improvement Using Hybrid Passive Filter Configuration for Wind Energy Systems

Wind energy conversion systems (WECS) which consist of wind turbines with permanent magnet synchronous generator (PMSG) and full-power converters have become widespread in the field of renewable power systems. Generally, conventional diode bridge rectifiers have used to obtain a constant DC bus voltage from output of PMSG based wind generator. In recent years, together advanced power electronics technology, Pulse Width Modulation (PWM) rectifiers have used in WECS. PWM rectifiers are used in many applications thanks to their characteristics such as high power factor and low harmonic distortion. In general, L, LC and LCL-type filter configurations are used in these rectifiers. These filter configurations are not exactly compensate current and voltage harmonics. This study proposes a hybrid passive filter configuration for PWM rectifiers instead of existing filters. The performance of hybrid passive filter was tested via MATLAB/Simulink environment under various operational conditions and was compared with LCL filter structure. In addition, neuro-fuzzy controller (NFC) was preferred to increase the performance of PWM rectifier in DC bus voltage control against disturbances because of its robust and nonlinear structure. The study demonstrates that the hybrid passive filter configuration proposed in this study successfully compensates current and voltage harmonics, and improves total harmonic distortion and true power factor.

Improved control configuration of PWM rectifiers based on neuro-fuzzy controller.

It is well-known that rectifiers are used widely in many applications required AC/DC transformation. With technological advances, many studies are performed for AC/DC converters and many control methods are proposed in order to improve the performance of these rectifiers in recent years. Pulse width modulation (PWM) based rectifiers are one of the most popular rectifier types. PWM rectifiers have lower input current harmonics and higher power factor compared to classical diode and thyristor rectifiers. In this study, neuro-fuzzy controller (NFC) which has robust, nonlinear structure and do not require the mathematical model of the system to be controlled has been proposed for PWM rectifiers. Three NFCs are used in control scheme of proposed PWM rectifier in order to control the dq-axis currents and DC voltage of PWM rectifier. Moreover, simulation studies are carried out to demonstrate the performance of the proposed control scheme at MATLAB/Simulink environment in terms of rise time, settling time, overshoot, power factor, total harmonic distortion and power quality.