Title :
Vector control of induction motor based on online identification and ant colony optimization
Author :
Chun-shan Lai ; Kai-xiang Peng ; Gui-shui Cao
Author_Institution :
Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
Abstract :
During operation, due to changes of temperature, magnetic field, frequency and other factors, electrical and mechanical parameters of induction motor will change. It will affect controlled plant model accordingly bring badly control accuracy directly. In order to obtain better dynamic performance and steady state accuracy, this paper proposes a combination method of online identification and online optimization of the controller parameters. It is designed that a vector control system of induction motor based on online identification and ant colony optimization. The simulation results have proved the effectiveness of this method. It can not only meet the real time induction motor vector control requirements, and also can greatly improve the induction motor dynamic performance and steady state characteristics, showing strong self-adaptability and robustness.
Keywords :
induction motors; machine vector control; optimisation; power system identification; self-adjusting systems; ant colony optimization; controlled plant model; induction motor; online identification; online optimization; robustness; self-adaptability; vector control; ACO; Induction Motor; LS; Vector Control;
Conference_Titel :
Industrial and Information Systems (IIS), 2010 2nd International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-7860-6
DOI :
10.1109/INDUSIS.2010.5565640