Modeling and Simulation of SRM DTC Control Based on RBF Neural Network and Fuzzy Adaptive PID Controller

被引：0
|
作者：
Song, Guiying [1 ]
Xue, Ruipeng [1 ]
Ling, Yuesheng [1 ]
Zuo, Nuan [1 ]
Huang, Wenmei [1 ]
机构：
[1] Hebei Univ Technol, Tianjin 13821468893, Peoples R China
来源：
2014 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO (ITEC) ASIA-PACIFIC 2014 | 2014年
关键词：
SRM; DTC; RBF Neural Network; fuzzy adaptive PID; simulation;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
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页数：4
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