New Model Reference Adaptive System Speed Observer for Field-Oriented Control Induction Motor Drives Using Neural Networks

Hossein Rahimi Khoei,Mahdi Zolfaghari

doi:10.11591/eei.v5i1.520

Abstract

One of the primary advantages of field-oriented controlled induction motor for high performance application is the capability for easy field weakening and the full utilization of voltage and current rating of the inverter to obtain a wide dynamic speed rangeThis paper describes a Model Reference Adaptive System (MRAS) based scheme using Artificial Neural Network (ANN) for online speed estimation of sensorless vector controlled induction motor drive. The proposed MRAS speed observer uses the current model as an adaptive model. The neural network has been then designed and trained online by employing a back propagation network (BPN) algorithm. The estimator was designed and simulated in Matlab/Simulink. Simulation result shows a good performance of speed estimator. The simulation results show good performance in various operating conditions. Also Performance analysis of speed estimator with the change in resistances of stator is presented. Simulation results show this estimator robust to parameter variations especially resistances of stator.

Highlights

Induction motors are electromechanical systems suitable for a large spectrum of industrial applications, due to its high reliability, relatively low cost, and modest maintenance requirements [1]
Artificial Neural Network advantages such as: ability to approximate arbitrary nonlinear mappings learning from the real system or the approximate intelligence and self-organizing capability possibility of parallel computing robustness ability to generalize and fault tolerance It is a major advantage of ANN based techniques that they do not require any mathematical model of the motor under consideration and the drive development time can be substantially reduced [4]
Speed Estimation using Neural Network In Model Reference Adaptive System (MRAS) technique, some state variables, Xd, Xq of the induction machine are estimated in a reference model and are compared with state variables Xd, Xq estimated by using an adaptive model

Summary

Introduction

Induction motors are electromechanical systems suitable for a large spectrum of industrial applications, due to its high reliability, relatively low cost, and modest maintenance requirements [1]. They have estimated speed from the instantaneous values of stator voltages and currents using induction motor model.

Results

Conclusion