Parameter Identification of Permanent Magnet Synchronous Linear Motors Using Multi-Innovation Least Squares Method
编号:414 访问权限:公开 更新:2021-06-27 20:16:09 浏览:1147次 张贴报告

报告开始:暂无开始时间(Asia/Shanghai)

报告时间:暂无持续时间

所在会场:[暂无会议] [暂无会议段]

摘要
The identification of dynamic model parameters of the permanent magnet synchronous linear motors (PMSLMs) is the foundation of high-performance motor control. To address the low accuracy of modelling of PMSLMs, a parameter identification method of the PMSLM is proposed by using multi-innovation least squares (MILS) approach in this paper. The linear transfer function of the PMSLM is first built. Then the MILS approach based on the recursive least squares (RLS) algorithm is developed to identify the parameters of the built model. Finally, the simulation results of MILS and RLS algorithms are shown, and the effectiveness of the proposed method is verified.
关键词
permanent magnet synchronous linear motors, system identification, multi-innovation recursive least squares method
报告人
Mou Hongda
Guangdong Key Laboratory of Electromagnetic Control and Intellignet Robots Shenzhen University

Hongda Mou is a graduate student from Shenzhen University. He is mainly engaged in the research of motor research in the field of chip manufacturing and rail transportation. He mainly studies the control and application of permanent magnet synchronous linear motors, magnetic levitation planar motors, and planar switched reluctance motors.

发表评论
验证码 看不清楚,更换一张
全部评论
重要日期
  • 会议日期

    07月01日

    2021

    07月04日

    2021

  • 07月03日 2021

    报告提交截止日期

  • 11月03日 2021

    注册截止日期

主办单位
Huazhong University of Science and Technology, China
协办单位
University of Sydney, Australia
Southwest Jiaotong University, China
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询