Dual Direct Torque Control of Doubly Fed Induction Machine using Artificial Neural Network

被引：0

作者：

Khadar, Saad ^{[1
]}

Kouzou, Abdellah ^{[1
]}

机构：

[1] Zian Achour Univ, Fac Technol, LAADI Lab, Djelfa 17000, Algeria

来源：

2018 3RD INTERNATIONAL CONFERENCE ON PATTERN ANALYSIS AND INTELLIGENT SYSTEMS (PAIS) | 2018年

关键词：

dual direct torque control; artificial neural network; switching tables; DFIM; MOTOR;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The main aim of the present paper focuses on the review and the development of the origin Direct Torque Control (DTC) approach which is applied on the doubly fed induction machine (DFIM). In this developed approach a novel DFIM control strategy is proposed based on the Dual Direct Torque Control (DDTC) using two ANN controllers to avoid the use of the switching tables. Indeed, the developed approach aims to ensure the minimization of the torque and to improve the motor performance. The simulation results show clearly that a significant improvement in the torque dynamic and in the flux responses are ensured when compared to the conventional direct torque control method.

引用

页码：54 / 60

页数：7

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