MRAS Speed Observer for High Performance Linear Induction Motor Drives based on Linear Neural Networks

被引：0
|
作者：
Accetta, Angelo [1 ]
Cirrincione, Maurizio [2 ]
Pucci, Marcello [1 ,3 ]
Vitale, Gianpaolo [3 ]
机构：
[1] Univ Palermo, Palermo, Italy
[2] Tech Univ, Belfort 90010, France
[3] ISSI CNR, Palermo, Italy
来源：
2011 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE) | 2011年
关键词：
Linear Induction Motor (LIM); Sensorless control; Model Reference Adaptive Systems (MRAS); Neural Networks (NN); Field Oriented Control (FOC); EQUIVALENT-CIRCUIT; VECTOR CONTROL; SENSORLESS;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
This paper proposes a Neural Network (NN) MRAS (Model Reference Adaptive System) speed observer suited for linear induction motor (LIM) drives. The voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been obtained. Then, equations of the induced part have been discretized and rearranged so as to be represented by a linear neural network the TLS EXIN neuron, which has been used to compute the machine linear speed on-line and in recursive form. The proposed NN MRAS observer has been tested experimentally on a suitably developed test setup. Its performance has been also compared to the classic MRAS speed observer.
引用
收藏
页码：1765 / 1772
页数：8
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