شماره ركورد كنفرانس :
144
عنوان مقاله :
Neural Adaptive Controller for Magnetic levitation System
پديدآورندگان :
Hajimani Masoud نويسنده , Alzahra Sanai Dashti Zohreh نويسنده , Gholami Milad نويسنده , Jafari Mohammad نويسنده Faculty of Natural Resources, Tehran University, Tehran, Iran
كليدواژه :
Magnetic levitation system , Neural network , RBF , Intelligent control
عنوان كنفرانس :
مجموعه مقالات دوازدهمين كنفرانس سيستم هاي هوشمند ايران
چكيده فارسي :
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.
شماره مدرك كنفرانس :
3817034
