Artificial Neural Network and Adaptive Neuro Fuzzy Control of Direct Torque Control of Induction Motor for Speed and Torque Ripple Control
2018
This paper presents Artificial Neural Networks (ANN) and Adaptive Neural-Fuzzy Inference System
(ANFIS) for reduction of torque and flux ripples in transient and steady state response of Direct Torque Control
(DTC) for Induction Motor drive. The Flux and Electromagnetic torque can be controlled by using efficient
Direct Torque Control (DTC) scheme This proposed technique is to improve the torque, speed and flux
response with the Artificial Neural Network (ANN) and then with the Adaptive Neuro-Fuzzy Inference
(ANFIS). This paper shows implementation of DTC system using ANN and ANFIS on three phase induction
motor to optimize the flux and to improve the performance of fast stator flux response in transient state. To
improve the performance of DTC with the modern technique using ANN and ANFIS approach is implemented
and performance of ANN DTC compared with CDTC and ANN DTC with ANFIS is done, conclusion is about
the ANN approach shows the better performance than CDTC and ANFIS shows superior performance than
ANN. The performance has been tested by using MATLAB/SIMULINK and NEURAL NETWORK toolbox
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