Study on Rotor Speed Identification of DTC System Based on PSO Algorithms of BP Neural Network

被引：0

作者：

Cao, Chengzhi ^{[1
]}

Lu, Yuanyuan ^{[1
]}

Wang, Fang ^{[1
]}

Zheng, Haiyin ^{[1
]}

机构：

[1] Shenyang Univ Technologyorganizat, Dept Informat Sci & Engn, Shenyang, Peoples R China

来源：

2009 IITA INTERNATIONAL CONFERENCE ON SERVICES SCIENCE, MANAGEMENT AND ENGINEERING, PROCEEDINGS | 2009年

关键词：

PSO algorithms; DTC system; rotor speed identification; BP neural network;

D O I：

10.1109/SSME.2009.157

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

To solve the strong randomicity and slow convergence of the Particle Swarm Optimization(PSO) algorithms, two new particle's position renewal formulas were analyzed on the basis of extrapolation in mathematics. A new modified PSO algorithms (called Leading PSO algorithms) was put forward. The Direct Torque Control(DTC) System was built in the environment of Matlab(Simulink). The weight and threshold values of BP Neural Network were trained using the modified PSO algorithms. Some disadvantages such as slow convergence speed and easily plunging into the local solution were avoided effectively. The simulation result shows that the system works well, and the rotor speed identifier has great static and dynamic performance.

引用

页码：594 / 597

页数：4

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