ADAPTIVE FUZZY LOGIC SPEED CONTROLLER WITH TORQUE ADAPTED GAINS FUNCTION FOR PMSM DRIVE

This paper presents a 15 rules-base Function Torque Adapted Gain Fuzzy Inference System (FTAGFIS) adaptive speed controller for the Permanent Magnet Synchronous Motor (PMSM). The proposed controller was developed using Adaptive Neuro Fuzzy Inference System (ANFIS). This expanded version of the FIS not only suggests the effectiveness of using the ANFIS to develop an adaptive speed controller for motors but also the effectiveness of the methodology that was employed to train the FIS. The simulation results of the developed FTAGFIS show superior speed tracking and recovery performance from motor parameter variations, load torque and speed disturbances, which indicates the ability of the PMSM to self- adapt itself to different operating conditions. The simulations were carried out in the MATLAB ® environment