Abstract: In order to have stable and high performance of direct torque and flux control (DTFC) of double star induction motor drive (DSIM), proper on-line adaptation of the stator resistance is very important. This is inevitably due to the variation of the stator resistance during operating conditions, which introduces error in estimated flux position and the magnitude of the stator flux. Error in the estimated stator flux deteriorates the performance of the DTFC drive. Also, the effect of error in estimation is very important especially at low speed. Due to this, our aim is to overcome the sensitivity of the DTFC to the stator resistance variation by proposing on-line fuzzy estimation stator resistance. The fuzzy estimation method is based on an on-line stator resistance correction through the variations of the stator current estimation error and its variations. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of the suggested algorithm control is to avoid the drive instability that may occur in certain situations and ensure the tracking of the actual stator resistance. The validity of the technique and the improvement of the whole system performance are proved by the results.
Abstract: Recent developments in Soft computing techniques,
power electronic switches and low-cost computational hardware have
made it possible to design and implement sophisticated control
strategies for sensorless speed control of AC motor drives. Such an
attempt has been made in this work, for Sensorless Speed Control of
Induction Motor (IM) by means of Direct Torque Fuzzy Control
(DTFC), PI-type fuzzy speed regulator and MRAS speed estimator
strategy, which is absolutely nonlinear in its nature. Direct torque
control is known to produce quick and robust response in AC drive
system. However, during steady state, torque, flux and current ripple
occurs. So, the performance of conventional DTC with PI speed
regulator can be improved by implementing fuzzy logic techniques.
Certain important issues in design including the space vector
modulated (SVM) 3-ะค voltage source inverter, DTFC design,
generation of reference torque using PI-type fuzzy speed regulator
and sensor less speed estimator have been resolved. The proposed
scheme is validated through extensive numerical simulations on
MATLAB. The simulated results indicate the sensor less speed
control of IM with DTFC and PI-type fuzzy speed regulator provides
satisfactory high dynamic and static performance compare to
conventional DTC with PI speed regulator.