A Comparative Analysis of Two Neural-Network-Based Estimators for Efficiency Optimization of an Induction Motor Drive

Abstract

A comparative analysis on vector-controlled induction motor drive with efficiency optimization using a neural-network-based and a model-losses-based approaches as flux estimator is presented in this paper. On-line estimators for rotor, stator resistances, and mutual inductance are included, two different neural networks were trained varying their inputs, and was used the losses-model-based estimator with some estimated and nominal parameters. Modeling and simulation results are presented to confirm the best performance approach