Title :
The Nonlinear Modeling of SRM with Improved RBF Network
Author :
Sun, Hexu ; Mi, Yanqing ; Dong, Yan ; Zheng, Yi ; Dong, Yanzong
Author_Institution :
Autom. & Electr. Eng. Dept., Hebei Univ. of Technol., Tianjin, China
Abstract :
The modeling of inductance of SRM (switched reluctance motor) using RBF (radial basis function) network can resolve the nonlinear problem of SRM effectively. But traditional RBF network easily bring problems such as local minimum value and slow convergent speed. In order to resolve these problems, two aspects of improvements with RBF network are given from structure and algorithm in this paper. Additionally, current PWM is regulated dynamically with inductance model. It is proved that the improved RBF network can achieve good convergent speed and control effect.
Keywords :
electric machine analysis computing; pulse width modulation; radial basis function networks; reluctance motors; RBF network; SRM; inductance model; nonlinear modeling; radial basis function; switched reluctance motor; Equations; Magnetic analysis; Magnetic flux; Pulse width modulation; Radial basis function networks; Reluctance machines; Reluctance motors; Saturation magnetization; Torque; Voltage; Convergent speed; PWM regulation; RBF network; SRM;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-5557-7
Electronic_ISBN :
978-0-7695-3852-5
DOI :
10.1109/ICINIS.2009.23