Model Reference Linear Adaptive Control of DC Motor Using Fuzzy Controller

This paper deals with the conventional model reference adaptive control (MRAC) and replaces conventional control technique such as PI control with model reference adaptive control scheme with fuzzy linear adaptation. The Model Reference Adaptive Control (MRAC) speed control systems do not achieve consistent satisfactory performance over wide range of speed demand, especially at low speed and there is no defined rule to guide designers to choose the adaptation gains. The fuzzy logic model reference adaptive control maintains satisfactory response irrespective of the magnitude of the inputs. It enhances the performance of the DC drive compared to conventional MRAC. The performance of the drive system, thus obtained, is forming a set of test conditions with model reference fuzzy adaptive control. The performance of the drive is tested for load disturbances along with reference model. This work also compares the performance of Model Reference Fuzzy Adaptive scheme over conventional MRAC. This work is carried out by using MATLAB-SIMULINK.