Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive

被引：11
|
作者：
Gutierrez-Villalobos, Jose M. [1 ]
Rodriguez-Resendiz, Juvenal [1 ]
Rivas-Araiza, Edgar A. [1 ]
Martinez-Hernandez, Moises A. [1 ]
机构：
[1] Univ Autonoma Queretaro, Lab Mecatron, Queretaro 76010, Mexico
来源：
SENSORS | 2015年 / 15卷 / 07期
关键词：
adaptive system; neural networks; on-line identification; adjustable speed driver; parameter estimation; FOC;
D O I：
10.3390/s150715311
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.
引用
收藏
页码：15311 / 15325
页数：15
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