Artificial Neural Network and Adaptive Neuro Fuzzy Control of Direct Torque Control of Induction Motor for Speed and Torque Ripple Control

Author(s):  
V. M. Venkateswara Rao ◽  
A. Anand Kumar
Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2176 ◽  
Author(s):  
Narongrit Pimkumwong ◽  
Ming-Shyan Wang

This paper presents the speed estimator for speed sensorless direct torque control of a three-phase induction motor based on constant voltage per frequency (V/F) control technique, using artificial neural network (ANN). The estimated stator current equation is derived and rearranged consistent with the control algorithm and ANN structure. For the speed estimation, a weight in ANN, which relates to the speed, is adjusted by using Widrow–Hoff learning rule to minimize the sum of squared errors between the measured stator current and the estimated stator current from ANN output. The consequence of using this method leads to the ability of online speed estimation and simple ANN structure. The simulation and experimental results in high- and low-speed regions have confirmed the validity of the proposed speed estimation method.


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