Kılıç, Bahadır (2004) Sensorless control of induction machine. [Thesis]
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Abstract
AC drives based on fully digital control have reached the status of a maturing technology in a broad range of applications ranging from the low cost to high performance systems. Continuing research has concentrated on the removal of the sensors measuring the mechanical coordinates (e.g. tachogenerators, encoders) while maintaining the cost and performance of the control system. Speed estimation is an issue of particular interest with induction motor electrical drives as the rotor speed is generally different from the speed of the revolving magnetic field. The advantages of sensorless drives are lower cost, reduced size of the machine set, elimination of the sensor cable and reliability. However, due to the high order and nonlinearity of the IM dynamics, estimation of the angle speed without the measurement of mechanical variables becomes a challenging problem. Variety of solutions has been proposed to solve this problem in the literature. In this thesis work, by combining the variable structure systems and Lyapunov designs a new sensorless sliding mode observer algorithm for induction motor is developed. A Lyapunov function is chosen to estimate the rotor flux of an induction motor under any initial condition based on the principle that the aim of the vector control of IM is to keep the rotor flux magnitude constant from zero to nominal speed. Additionally, an observer estimating the rotor speed and the rotor time constant of the machine simultaneously has been proposed that stems from the flux estimation. The proposed method is very suitable for closed loop high-performance sensorless drives and it is believed that with its new approach it will help many researchers in their further work in the field of sensorless vector control of IM.
Item Type: | Thesis |
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Subjects: | T Technology > TJ Mechanical engineering and machinery |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics Faculty of Engineering and Natural Sciences |
Depositing User: | IC-Cataloging |
Date Deposited: | 18 Apr 2008 10:00 |
Last Modified: | 26 Apr 2022 09:43 |
URI: | https://research.sabanciuniv.edu/id/eprint/8209 |