Direct Torque Control Berbasis Adaptive Neuro Fuzzy Inference System Untuk Pengendali Kecepatan Motor Induksi - Pradana, Tommy Nana (Fakultas Teknik dan Ilmu Kelautan, Universitas Hang Tuah, 2023)
Induction motors are the motors are widely used in the industrial world, in addition to relatively low prices, easy maintenance. This motor has a good Traffic on rotational speed. The weakness of this motor is at that point in the load torque, the motor speed will change. In writing this thesis discussed the induction motor speed control system with the method of DTC (Direct Torque Control) that can provide rapid response in the event of changes in the load torque so the motor stays on steady footing steate and will return position at setpoint quickly. To obtain performance speed control of three phase induction motors with the method of DTC (direct torque control) requires a good control system, meaning that the control system that can follow changes in speed (setpoint) quickly. Thus the speed control of three-phase induction motor using DTC (direct torque control) was developed using intelligence control ANFIS (Adaptive Neuro Fuzzy Inference System). The results of the simulation with Simulink shows that the controller ANFIS control induction motor speed does not load at start overshoot 0.7%, rise time of 1 second and setling time 1.1 seconds for a speed reference 1800 rpm, and when given the burden of 20nm overshooting 12:27% on the speed reference 1500rpm. By using Direct Torque Control (DTC) based Adaptive Neuro Fuzzy Inference System (ANFIS) were able to keep pace with the dynamic reference well and can suppress ripple down to a very low level.