Neural Network Adaptive State Feedback Control of a Magnetic Levitation System

摘要：

　　Magnetic levitation system is a typical nonlinear and instable system.Based on the complexity and inaccuracy of modelling,in this paper identified magnetic levitation system using the speciality that neural network(NN)can approach any nonlinear function.A Radial Basis Function neural network(RBFNN)controller is designed based on the neural network adaptive control principle.This paper proposes a control method which combine neural network adaptive control method and state feedback control method based on RBFNN.A simulation of the system is is proposed,and the result shows that RBFNN could approach magnetic levitation system very well,neural network adaptive state feedback controller has a good effect on this nonlinear system; this control system has a preferable stability and control property.

关键词： Radial Basis Function (RBF) neural network control state feedback magnetic levitation system

作者: Shi-tie Zhao Xian-wen Gao

作者单位: School of Information Science & Engineering,Northeastern University,Shenyang 110819

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 1602-1605

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）