Recurrent Fuzzy Neural Network for DC-Motor Control

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.