Magnetic Bearing Rotor Displacement Estimation Using O-RLS-SVM

摘要：

A new approach for magnetic bearing rotor dis placement estimation using on-line recursive least squares support vector machine (O-RLS-SVM) is proposed. The basic premise of the method is that an O-RLS-SVM forms a very efficient mapping structure for the non-linear magnetic bearing. Through measurement of the phase flux linkages and phase currents the O-RLS-SVM is able to estimate the rotor displacement, thereby facilitating elimination of the rotor displacement sensor. The O-RLS-SVM training data set is comprised of magnetization data for the magnetic bearing with equivalent flux linkage and equivalent current as inputs and the corresponding displacement as output. Given an updating training sample set, the O-RLS-SVM could build up an appro priate adaptive SVM architecture to express the dynamic be havior of magnetic bearing. This paper presents the develop ment, implementtation, and operation of O-RLS-SVMbased displacement estimator for a three-phase AC active magnetic bearing.

关键词： magnetic bearing on-line recursive least squares support vector machine displacement estimation sensorless control

作者: Zhu Zhiying Sun Yukun

作者单位: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013 Jiangsu Province, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 727-731

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）