Neural Adaptive controller for Magnetic levitation system

Author

Hajimani, Masoud ; Dashti, Zohreh Alzahra Sanai ; Gholami, M. ; Jafari, Mohsen ; Shoorehdeli, Mahdi Aliyari

Author_Institution

Dept. of Electr. Eng., Islamic Azad Univ., Qazvin, Iran

fYear

2014

fDate

4-6 Feb. 2014

Firstpage

1

Lastpage

6

Abstract

In this study a Neural Adaptive method is used for position control and identification of a Magnetic levitation system. This controller consists of three parts: PID controller, radial basis function (RBF) network controller and radial basis function (RBF) network identifier. The combination of controllers produces a stable system which adapts to optimize performance. It is shown that this technique can be successfully used to stabilize any chosen operating point of the system. All derived results are validated by computer simulation of a nonlinear mathematical model of the system.

Keywords

adaptive control; identification; magnetic levitation; neurocontrollers; position control; three-term control; PID controller; RBF network controller; RBF network identifier; computer simulation; magnetic levitation system; neural adaptive controller; nonlinear mathematical model; position control; radial basis function network controller; radial basis function network identifier; Adaptive control; Biological neural networks; Control systems; Magnetic levitation; Mathematical model; Intelligent Control; Magnetic levitation system; Neural Network; RBF;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems (ICIS), 2014 Iranian Conference on

Conference_Location

Bam

Print_ISBN

978-1-4799-3350-1

Type

conf

DOI

10.1109/IranianCIS.2014.6802530

Filename

6802530