MRAS speed estimator with fuzzy and PI stator resistance adaptation for sensorless induction motor drives using RT-lab

Perspectives in science Pub Date : 2016-09-01 DOI:10.1016/j.pisc.2016.04.013

S. Mohan Krishna, J.L. Febin Daya

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引用次数: 30

Abstract

This paper presents a real-time simulation study of Model Reference Adaptive System based rotor speed estimator with parallel stator resistance adaptation mechanism for speed sensorless induction motor drive. Both, the traditional Proportional Integral and Fuzzy logic based control mechanisms are utilised for stator resistance adaptation, while, the rotor speed is estimated parallely by means of Proportional Integral based mechanism. The estimator's response to dynamic changes in Load perturbation and doubling of the nominal value of the actual stator resistance of the motor is observed. The superiority of the fuzzy based stator resistance adaptation in the Model Reference Adaptive System estimator is proved through results validated in real-time. The purpose of employing a fairly new real-time platform is to reduce the test and prototype time. The model is initially built using Matlab/Simulink blocksets and the results are validated in real time using RT-Lab. The RT-lab blocksets are integrated into the Simulink model and then executed in real-time using the OP-4500 target developed by Opal-RT. The real-time simulation results are observed in the workstation.

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MRAS速度估计与模糊和PI定子电阻自适应无传感器感应电机驱动使用RT-lab

本文对无速度传感器异步电动机驱动中基于模型参考自适应系统的并联定子电阻自适应转子转速估计器进行了实时仿真研究。传统的比例积分控制和基于模糊逻辑的控制都用于定子电阻的自适应，而基于比例积分的机构则用于转子转速的并行估计。观察了估计器对负载扰动动态变化和电机定子实际电阻标称值加倍的响应。仿真结果表明，基于模糊的定子电阻自适应方法在模型参考自适应系统估计器中的优越性。使用一个相当新的实时平台的目的是减少测试和原型时间。该模型最初使用Matlab/Simulink块集构建，并使用RT-Lab实时验证结果。RT-lab块集集成到Simulink模型中，然后使用Opal-RT开发的OP-4500目标实时执行。在工作站上实时观察仿真结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Perspectives in science

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