DocumentCode :
2995757
Title :
Commutation signal identification for switched reluctance motors based on fuzzy neural networks
Author :
Changliang Xia ; Fuchen Jia ; Mei Xue ; Hongwei Fang
Author_Institution :
Sch. of Electr. Eng. & Autom., Tian Jin Univ., Tianjin
fYear :
2008
fDate :
1-3 Sept. 2008
Firstpage :
700
Lastpage :
704
Abstract :
This paper presents a new approach of position sensorless control for switched reluctance motors (SRM) based on fuzzy neural networks (FNN). In this method, two different modules are established to identify phase commutation signals during the starting period and steady running period respectively. In each module, FNNs are used to map the relationship of phase current, flux linkage and phase commutation signals. Commutation signals for each phase are identified continuously by two FNNs. One of them estimates the turn-on signal; the other identifies the turn-off signal. Once the motor reaches the given speed, commutation signals will be provided by the steady running module instead of the starting module. The simulation results show that this method can exactly achieve phase commutation identification, and the system can operate steadily with the proposed position sensorless control method.
Keywords :
commutation; fuzzy control; machine control; neurocontrollers; position control; reluctance motors; commutation signal identification; flux linkage; fuzzy neural network; phase commutation signal; phase current; starting module; steady running module; switched reluctance motor; turn-off signal; turn-on signal; Commutation; Couplings; Fuzzy control; Fuzzy neural networks; Neural networks; Reluctance machines; Reluctance motors; Rotors; Sensorless control; Signal processing; Fuzzy neural network (FNN); Switched reluctance motor (SRM); phase commutation signals; position sensorless control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-2502-0
Electronic_ISBN :
978-1-4244-2503-7
Type :
conf
DOI :
10.1109/ICAL.2008.4636239
Filename :
4636239
Link To Document :
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