The DTNN Identification Model of Magnetic Bearing Supporting System

摘要：

The neural networks DTNN identification model is developed on the basis of the force analysis of magnetic bearing spindle.Which reflects the nonlinear delay character between inputs and outputs system.This network is able to converge quickly in 5 training steps.The mean square error value reduces to 3.495e-006 in 50 steps.Inspection shows that the neural networks DTNN identification model can fit the I/O character of the magnetic bearing supporting system within a permitted error range.This paper proposes a new approach for magnetic bearing system modeling.

作者: A.Zhang Maoqing B.Yu Zhongcheng C.Qu Haini D.SunYong

会议类型: 国际会议

会议名称: The International Conference Information Computing and Automation(2007国际信息计算与自动化会议)

会议地点: 成都

会议语种:英文

页码: 1379-1382

在线出版日期: 2007-12-19（万方平台首次上网日期，不代表论文的发表时间）