Title :
Modeling and simulation of SRM DTC control based on RBF Neural Network and Fuzzy Adaptive PID Controller
Author :
Guiying Song ; Ruipeng Xue ; Yuesheng Ling ; Nuan Zuo ; Wenmei Huang
Author_Institution :
Hebei Univ. of Technol., Tianjin, China
fDate :
Aug. 31 2014-Sept. 3 2014
Abstract :
In the conventional DTC system of SRM, due to the defects of complex computation cause time delay and the SRM are nonlinear, variable structures, RBF Neural Network (RBFNN) and Fuzzy Adaptive PID Controller are applied to DTC control system of SRM in the paper. Conventional state selector is replaced by RBFNN; fuzzy adaptive PID controller is used to adjust speed. The simulations show that the new system performance better.
Keywords :
adaptive control; discrete cosine transforms; fuzzy control; machine control; neural nets; radial basis function networks; reluctance motor drives; three-term control; RBF neural network; SRM DTC control; fuzzy adaptive PID controller; Adaptation models; Adaptive systems; Biological neural networks; Niobium; Reluctance motors; Torque control; DTC; RBF Neural Network; SRM; fuzzy adaptive PID; simulation;
Conference_Titel :
Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-4240-4
DOI :
10.1109/ITEC-AP.2014.6941265
