Title :
Nonlinear control of a DC-motor based on radial basis function neural networks
Author :
Ninos, Konstantinos ; Giannakakis, Charalampos ; Kompogiannis, Ioannis ; Stavrakas, Ilias ; Alexandridis, Alex
Author_Institution :
Dept. of Electron., Technol. Educ. Inst. of Athens, Athens, Greece
Abstract :
This paper presents a nonlinear controller based on an inverse neural network model of the system under control. The neural controller is implemented as a Radial Basis Function (RBF) network trained with the powerful fuzzy means algorithm. The resulting controller is tested on a nonlinear DC motor control problem and the results illustrate the advantages of the proposed approach.
Keywords :
DC motors; fuzzy set theory; machine control; neurocontrollers; nonlinear control systems; radial basis function networks; fuzzy means algorithm; inverse neural network model; nonlinear DC motor control problem; nonlinear control; radial basis function neural network; Artificial neural networks; Biological neural networks; DC motors; Input variables; Predictive models; Radial basis function networks; Training; Fuzzy Means; Intelligent Control; Neural Controller; Neural Networks; Radial Basis Function;
Conference_Titel :
Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
978-1-61284-919-5
DOI :
10.1109/INISTA.2011.5946168
