PERFORMANCE IMPROVEMENT OF DIRECT TORQUE CONTROL FOR SWITCHED RELUCTANCE MOTOR USING NEURO-FUZZY CONTROLLER

被引：2
|
作者：
Veena, P.
Jeyabharath, R.
Rajaram, M.
机构：
[1] Department of EEE, K.S. Rangasamy College of Technology, Tamilnadu
[2] Department of EEE, Government College of Engineering, Tamilnadu, Tirunelveli
来源：
CONTROL AND INTELLIGENT SYSTEMS | 2010年 / 38卷 / 03期
关键词：
Direct torque control; flux control; neuro-fuzzy controller; switched reluctance motor;
D O I：
10.2316/Journal.201.2010.3.201-2118
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Direct torque control (DTC) of switched reluctance motor is known to have simple control structure with comparable performance to that of field-oriented control techniques. However, the role of optimal selection of the voltage space vector is one of the weakest points in a conventional DTC drive. In this paper, optimal selection of voltage space vectors is achieved using neuro-fuzzy controller. The proposed neuro-fuzzy controller's structure guides the torque and stator flux error signals through the fuzzy inference to get an output that takes the form of space voltage vector. flux response with minimized torque and flux ripple. Simulation results validate the proposed intelligent system with fast torque and
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页码：156 / 163
页数：2
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