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A Torque Estimation and Switching Angle Control of SRM using Neural Network  

백원식 (영남대학 대학원 전기공학과)
김민회 (영남이공대학 전기자동화과)
김남훈 (영남대 대학원 전기공학과)
최경호 (경북전문대학)
김동희 (영남대 전기전자공학부)
Publication Information
The Transactions of the Korean Institute of Power Electronics / v.7, no.6, 2002 , pp. 509-516 More about this Journal
Abstract
This paper presents a simple torque estimation method and switching angle control of Switched Reluctance Motor(SRM) using Neural Network(NN). SRM has gaining much interest as industrial applications due to the simple structure and high efficiency. Adaptive switching angle control is essential for the optimal driving of SRM because of the driving characteristic varies with the load and speed. The proper switching angle which can increase the efficiency was investigated in this paper. NN was adapted to regulate the switching angle and nonlinear inductance modelling. Experimental result shows the validity of the switching angle controller.
Keywords
SRM; Torque Estimation Method; Neural Network; Adaptive Switching Angle Control;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
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