Title :
Recurrent Fuzzy Neural Network for DC-Motor Control
Author :
Faramarzi, Ahmad ; Sabahi, Kamel
Author_Institution :
Ardabil Branch, Dept. of Electr. Eng., Islamic Azad Univ., Ardabil, Iran
Abstract :
In this paper recurrent fuzzy neural network (RFNN) is used for speed tracking of nonlinear Dc motor. The RFNN posses both the advantages of fuzzy logic and neural networks, reasoning and learning, and have memory in its structures that act as a memory for store past information. Also, this controller acts as nonlinear and adaptive controller, too. Some simulation results are done for indicating the priority of proposed method.
Keywords :
DC motors; adaptive control; angular velocity control; fuzzy neural nets; machine control; neurocontrollers; nonlinear control systems; recurrent neural nets; DC motor control; adaptive controller; nonlinear DC motor; nonlinear controller; recurrent fuzzy neural network; speed tracking; Adaptive control; DC motors; Fuzzy control; Fuzzy neural networks; Torque; Trajectory; RFNN; adaptive control; dc motor; direc method;
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2011 Fifth International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4577-0817-6
Electronic_ISBN :
978-0-7695-4449-6
DOI :
10.1109/ICGEC.2011.31
