Model Reference based Neuro-Fuzzy Control of DC Servo Motor


This paper presents a Neuro-Fuzzy approach for the D.C. servo motor, within the Model Reference Adaptive Control (MRAC) framework. To tackle the plant parameters variation, an adaptive algorithm is derived to tune a designed fuzzy controller such that the system output follows a desired output for stable reference model. The simulation result shows no oscillation in response and the time for reaching the desired position is very short with zero steady state errors. Based on the simulation results using MATLAB/SIMULINK package, it is found that the Neuro-fuzzy controller can be a viable choice for a networked control system due to its robustness against parameter uncertainty