Ph.D. Tezi Görüntüleme

Student: Mustafa AKTAŞ
Supervisor: Asst. Prof. Dr. Halil İbrahim OKUMUŞ
Department: Electrical and Electronics Engineering
Institution: Graduate School of Natural and Applied Sciences
University: Karadeniz Technical University, Turkey
Level: Ph.D.
Acceptance Date: 30/1/2006
Number of Pages: 149
Registration Number: i521

       In this study, mathematical analysis of techniques which have been proposed to improve Direct Torque Controlled Induction Motors results of computer simulation and experimental studies are presented.

In the first chapter of the study, the traditional methods and basic definitions have been given.

       The second chapter of the thesis is composed of four parts. In the first part, especially in low speeds, a solution to decrease the impacts of the stator resistive voltage drop on the DTC has been proposed. For this purpose, MRAS based Artificial Neural Network estimator has been suggested.

In the second part of the chapter, an Adaptive Hysteresis Band method has been proposed in order to get costant switching frequency for the DTC drive. With this method, the flux locus becomes circle in low speeds and switching losses decreases in high speeds.

       In the third part of the chapter, a speed estimation has been performed using the sliding mode control technique to constitute an Induction Motor Drive without a sensor.

In the last part of the chapter, a drive system which has been built to realize the experimental applications of all proposed methods has been described in details. In this study, a new motor drive has been implemented using TMS320C6711 DSP module for the purpose of applying the suggested techniques experimentally.

       By using DSP which is a very fast processor, the problem under the motor can be found out earlier and so, the control process can be increased. TMS32016711 DSP module has been used for the first time in our study. The results of simulations of the proposed methods have been justified by experimental results.


Direct Torque Control, Induction Motor, Artificial Neural Network, Model Reference Adaptive System, Adaptive Hysteresis Band, Sliding Mode Control, TMS320C6711, DSP Application.