DocumentCode :
2711033
Title :
Design, modeling, and position control of a single-phase reluctance machine
Author :
Leng, Siyu ; Liu, Wenxin ; Chung, II-Yop ; Cartes, David ; Edrington, Chris S.
Author_Institution :
Center for Adv. Power Syst. (CAPS), Florida State Univ., Tallahassee, FL, USA
fYear :
2009
fDate :
14-19 June 2009
Firstpage :
1758
Lastpage :
1763
Abstract :
This paper discusses the whole design process of a position control system of a single-phase reluctance machine under mechanical and electrical constraints. A MIMO Neural network is used to model the nonlinear properties of the machine. Based on it, a neural network based control scheme is developed to precisely control the rotor position of the designed single-phase reluctance machine. Simulation results show that a MIMO neural network model can effectively capture the nonlinear characteristics of the designed machine and the proposed neural network control scheme can control the rotor position precisely.
Keywords :
design; machine control; neurocontrollers; position control; reluctance machines; MIMO neural network; design process; electrical constraint; mechanical constraint; neural network based control scheme; nonlinear properties; position control system; rotor position; single-phase reluctance machine; Fluid flow control; Fuels; MIMO; Neural networks; Position control; Process design; Reluctance machines; Rotors; Torque; Valves;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
ISSN :
1098-7576
Print_ISBN :
978-1-4244-3548-7
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2009.5178867
Filename :
5178867
Link To Document :
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