Performance Enhancement of Sensorless Speed Control of DSIM Using MRAS and EKF Optimized by Genetic Algorithm

Autor: Katia Kouzi, Aissa Ameur, K. Sahraoui
Rok vydání: 2018
Předmět:
Zdroj: 2018 International Conference on Applied Smart Systems (ICASS).
DOI: 10.1109/icass.2018.8651996
Popis: In this paper, an efficient control of the dual-stator induction motor (DSIM) using indirect vector control and elaborated by different observers to estimate the rotor flux and the rotor speed. After presenting Park model of the DSIM, we applied the field oriented control (FOC) to decoupling the flux and the electromagnetic torque to control the speed of the machine which is fed by a cascade of two voltage inverters on three levels. Secondly, the same control structure of the indirect vector control is used, but, we introduced model reference adaptive system (MRAS) and an extended Kalman filter (EKF) to estimate the rotor flux, the rotor speed and both stator and rotor resistance of the machine for speed sensor less control purposes. Finally the Simulations with genetic algorithms show that the results are very encouraging and achieve good performances.
Databáze: OpenAIRE