Paper Title :Performance Analysis of PMSM Drive using Artificial Neural Network and Bacterial Foraging Optimization Techniques

Author :Deepti Yadav, Frank Tittel, Arunima Verma

Article Citation :Deepti Yadav ,Frank Tittel ,Arunima Verma , (2020 ) " Performance Analysis of PMSM Drive using Artificial Neural Network and Bacterial Foraging Optimization Techniques " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 25-30, Volume-8,Issue-6

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

Type : Research paper

Published : Volume-8,Issue-6

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