Real-time neuro-fuzzy control based on internal model applied to a DC motor

This paper presents the development of the inverse as well the internal model of a direct current motor. The models are identified by adaptive neuro-fuzzy inference system (ANFIS). The identification is done in real-time and it includes the data collect experiment, the ANFIS type system training and the validation with new data. On the other hand, we include the control system design based on neuro-fuzzy modeling. The closed loop control is able to correct errors of generated model or to correct those errors caused by any possible disturbance at the output of equipment.