Title :
Application of Fuzzy Neural Network in Direct Torque Control System
Author :
Liping Fan ; Bin Li
Author_Institution :
Shenyang Inst. of Chem. Technol., Shenyang
fDate :
May 30 2007-June 1 2007
Abstract :
Induction motors have some inherent characteristics such as multivariate, parameter indeterminacy, strong coupling and non-linearity. These bring about a lot of trouble to the induction motor drive system. Considering the problems of AC speed regulation cause by the motor´s inherent characteristics, a fuzzy control strategy based on the RBF neural network was presented. It was designed to make full use of the features of RBF neural network and fuzzy control. A contrastive research was made between the conventional direct torque control system and the fuzzy control system based on RBF. Simulation results show that the fuzzy control strategy based on RBF for direct torque control System has strong robustness, quick response, low overshot.
Keywords :
angular velocity control; control engineering computing; electric machine analysis computing; fuzzy control; fuzzy neural nets; induction motor drives; machine control; radial basis function networks; torque control; AC speed regulation; RBF neural network; direct torque control system; fuzzy control; fuzzy neural network; induction motor drive system; parameter indeterminacy; Artificial neural networks; Automation; Control systems; Error correction; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Neural networks; Stators; Torque control; RBF neural network; direct torque control; fuzzy control; stator Resistance Observer;
Conference_Titel :
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-0817-7
DOI :
10.1109/ICCA.2007.4598816
