WSEAS Transactions on Power Systems
Print ISSN: 1109-9445, E-ISSN: 2415-1513
Volume 11, 2016
Sensorless Fuzzy Sliding Mode Speed Controller for Induction Motor with DTC Based on Artificial Neural Networks
Authors: , , , ,
Abstract: The objective of this work is to develop a Fuzzy Sliding Mode Speed Controller and to replace the conventional selector switches of the voltage inverter by a selector based on Artificial Neural Networks (ANNs) for the induction motor drive. The Direct Torque Control (DTC) is known to produce quick and robust response in AC drive system. However, during steady state, torque, flux and current ripple occurs. An improvement of electric drive system can be obtained using a DTC method based on ANNs which reduces the torque and flux ripples. The rotor speed and stator flux are estimated by the model reference adaptive system (MRAS) scheme which is determined from measured terminal voltages and currents. The speed loop is carried out by a Fuzzy Sliding Mode Controller (FSMC) giving high performance and robustness to the drive system. The MATLAB SIMULINK is used to perform the simulation. The simulated results of this method are discussed and compared with conventional DTC.
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Pages: 72-80
WSEAS Transactions on Power Systems, ISSN / E-ISSN: 1109-9445 / 2415-1513, Volume 11, 2016, Art. #10