Title :
Self-tuning speed controller for induction motor drives
Author :
Oh, Won Seok ; Sol, Kim ; Cho, Kyu Min ; Yoo, Kyungsang ; Kim, Young Tae
Abstract :
A genetic based self-tuning speed controller is proposed for the high-performance drives of induction motors. Nonlinear system identification of a motor drive system is required and the results of system identification could provide the controller with information regarding the load variation, system noise, and parameter variation of the induction. The proposed self-tuning controller can change the gains of the controller according to system conditions. For the estimation of system parameters, a genetic algorithm is used. A self-tuning controller is designed that is adequate for the speed control of the induction motor. The availability of the proposed controller is verified.
Keywords :
angular velocity control; genetic algorithms; induction motor drives; load (electric); machine control; nonlinear systems; self-adjusting systems; genetic algorithm; induction motor drives; load variation; nonlinear system identification; off-line estimation; parameter variation; self-tuning speed controller; speed control; system noise; Control systems; Genetic algorithms; Induction motors; Load management; Mathematical model; Optimization; Torque; genetic algorithm; induction motor; load variation; off-line estimation; self-tuning;
Conference_Titel :
Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), 2012 International Symposium on
Conference_Location :
Sorrento
Print_ISBN :
978-1-4673-1299-8
DOI :
10.1109/SPEEDAM.2012.6264455
