Performance analysis of PMSM drive using Artificial Neural Network technique

Abstract

This paper is describing Artificial Neural Network (ANN) technique using a nonlinear speed controller design Permanent-Magnet-Synchronous-Motor (PMSM) methodology, where more emphasis is given to the tuning of the PID controller. Subsequently, speed control for PMSM was analyzed in depth using ANN techniques to enhance the performance parameters in terms of integral-gain (Ki), derivative-gain (Kd) and proportional gain (Kp). Besides this, the performance of overall-system is analyzed under different-operating scenario that includes, braking, starting, load-application and load-removal conditions. Moreover, the comparison between speed-control of PMSM with the ANN technique and speed control of PMSM using Ziegler-Nichols (Z-N) method are discussed in depth. These analyses are evaluated in-terms of static and dynamic-response. The transient-response is examined in terms of rise-time (tr), settling-time (ts), peak-time (tp), and peak-overshoot (Mp). Where, overall performance of PID speed-controller with Artificial-Neural-Network technique depicts that the proposed method is enhanced the performance under the different operating scenarios.