Modeling and Experimental Verification of ANN Based Online Stator Resistance Estimation in DTC-IM Drive
نویسندگان
چکیده
Direct Torque controlled induction motor (DTC-IM) drives use stator resistance of the motor for stator flux estimation. So, stator resistance estimation properly is very important for a stable and effective operation of the induction motor. Stator resistance variations because of changing in temperature make DTC operation difficult mainly at low speed. A method based on artificial neural network (ANN) to estimate the stator resistance online of IM for DTC drive is modeled and verified in this paper. To train the neural network a back propagation algorithm is used. Weight adjustment of neural network is done by back propagating the error signal between measured and estimated stator current. An extensive simulation has been carried out in MATLAB/SIMULINK to prove the efficacy of the proposed stator resistance estimator. The simulation & experimental result reveals that proposed method is able to obtain precise torque and flux control at low speed.
منابع مشابه
Stator resistance estimation scheme using fuzzy logic system for direct torque controlled induction motor drive
Direct Torque controlled induction motor (DTC-IM) drives have been used widely over last few decades. DTC-IM drives use the stator resistance of the motor for stator flux estimation which directly depends on the stator resistance of IM. Proper estimation of the stator resistance is very important because stator resistance varies due to the increase in temperature of the machine during operation...
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