Title :
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
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;
Conference_Titel :
Intelligent Systems (ICIS), 2014 Iranian Conference on
Conference_Location :
Bam
Print_ISBN :
978-1-4799-3350-1
DOI :
10.1109/IranianCIS.2014.6802530
