Abstract:
Sensorless speed control of Permanent Magnet Synchronous Motor (PMSM) is
still in development stage to overcome the existing drawbacks such as speed rip ples, torque ripples and poor performance at low speeds with no-load or lightly
loaded conditions. In this thesis, sensorless Field Oriented Control (FOC) system
which is based on artificial neural network (ANN) implementation is proposed.
The control system uses ANN aided Model Reference Adaptive System (MRAS)
for speed estimation. Both the speed estimator and the controller of the proposed
system use ANN based implementations. The performance of the proposed sys tem is analyzed for speed control of PMSM, for various speed and load torque
values. The simulation results of the proposed ANN based speed estimator and
controller model demonstrate that ANN aided MRAS based controller of PMSM
has the capability to enhance the performance of the system. Specifically, it re duces the overall complexity and initial speed overshoot by 1% as compared to
the conventional PI based MRAS controllers employed for PMSM speed control.
It has acceptable settling and rise time in its dynamic response.
