Modeling and simulation of Adaptive Neuro-Fuzzy controller for Chopper-Fed DC Motor Drive

The classical controllers algorithm is both simple and reliable, and has been applied to thousands of control loops in various industrial applications over the past 60 years (89%-90% of applications). This paper presents the neuro-fuzzy controller incorporates fuzzy logic algorithm with a five-layer artificial neural network (ANN) structure. The conventional controller is replaced by Adaptive Neuro-Fuzzy Inference System (ANFIS) before that made the identification process of ANFIS controller by the data base of classical controller to be consider as initial condition for controlling process with this system. The simulation of the design is achieved by using Matlab Ver. 2010a. Chopper-Fed DC Motor Drive (Continuous / Discrete) are consider as case study. Satisfactory results are obtained explaining the ability of ANFIS controller to control with the dynamic high nonlinear system and can be get very good results by tunes the fuzzy controller.