A BP Neural Network Controller for Magnetic Suspended Flywheel System

摘要：

A BP neural network controller is proposed for direct suspending control for Magnetic Suspended Flywheel System (MSFS) that is supported by Active Magnetic Bearings (AMB). A one hidden layer configuration is adopted in the BP neural network, and the back propagated algorithm for network weights updating is derived based on AMB’s linear model. The discussed controller is implemented in the MSFS with random initial network weights, and it is trained online as the whole system operated. Simulations show the proposed BP neural network controller is apt to succeed in suspending the flywheel, and better performances such as precise position control, disturbance rejection, vibration suppression and quiet control are achieved under power consumption limitation. The results validate the feasibility and effectiveness of the presented BP neural network controller.

关键词： Magnetic Suspended Flywheel System Active Magnetic Bearing BP Neural Network Disturbance Rejection Vibration Suppression

作者: Chen Xiaofei Liu Kun

作者单位: Coll. of Aerospace and Material Eng., National Univ. of Defense Tech., Changsha, China

会议类型: 国际会议

会议名称: The Twelfth International Symposium on Magnetic Bearings(第十二届国际磁悬浮轴承学术会议)

会议地点: 武汉

会议语种:英文

页码: 317-324

在线出版日期: 2010-08-22（万方平台首次上网日期，不代表论文的发表时间）