Sensorless Control of Switched Reluctance Generator Drive Based on Neural Networks

摘要：

In this paper, the analysis, design, and implement- tation of a novel rotor position estimator for the control of switched reluctance generator(SRG) are presented. The rotor position is obtained by the improved minimal neural networks (NNs) whose inputs are the average phase current and the flux linkage. The flux linkage is calculated by flux integrator. Compared with the traditional NNs, it is demonstrated that a minimal NNs is easy to operate and attainable on a low-cost DSP. Experimental verification of the proposed control system applied to a wind energy conversion system is provided to demonstrate that the motor drive system has a small error of location observation and a good performance in generating operation. The control system of sensorless switched reluctance generator is simple, reliable and applicable to some harsh environments such as wind energy.

关键词： Neural Networks (NNs) switched reluctance generator wind power generation sensorless control

作者: Guojun Tan Guangchao Li Yanping Zhao Songyan Kuai Xulong Zhang

作者单位: School of Information and electrical Engineering,China University of Mining and technology,Xuzhou,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）