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: In this paper a sliding-mode torque and flux control is
designed for encoderless synchronous reluctance motor drive. The
sliding-mode plus PI controllers are designed in the stator-flux field
oriented reference frame which is able to track the mentioned
reference signals with a minimum pulsations in the state condition. In
addition, with these controllers a fast dynamic response is also
achieved for the drive system. The proposed control scheme is robust
subject to parameters variation except to stator resistance. To solve
this problem a simple estimator is used for on-line detecting of this
parameter. Moreover, the rotor position and speed are estimated by
on-line obtaining of the stator-flux-space vector. The effectiveness
and capability of the proposed control approach is verified by both
the simulation and experimental results.