Paper Title
Performance Analysis of PMSM Drive using Artificial Neural Network and Bacterial Foraging Optimization Techniques
Abstract
This paper describes the performance of a Permanent Magnet Synchronous Motor (PMSM) drive using an
Artificial Neural Network (ANN) and Bacterial foraging optimization (BFO) techniques used for controlling the speed of the
PMSM drive. In addition, an important task is to improve the performance of the PMSM drive by minimizing the speed and
torque ripples that cause noise and vibrations. Moreover, the performance is further enhanced by improving the transient
response specifications during the various operating modes. The transient response specifications considered in this analysis
are rise-time, peak-time, settling time and peak overshoot. Consequently, this work has provided an insight into the
incorporation of the ANN and BFO techniques for tuning and designing of a smart speed controller in the PMSM drive
model.
Keywords - PMSM, Ziegler-Nichols, Ann, Bacterial Foraging Optimization