DESAIN OPTIMASI KECEPATAN MOTOR INDUKSI MENGGUNAKAN HYBRID ANFIS (ADAPTIVE NEURO FUZZY INFERENCE SYSTEM) DENGAN PID-PSO (PROPORTIONAL INTEGRAL DERIVATIVE – PARTICLE SWARM OPTIMIZATION) CONTROLLER

Sari

The stator coil gets three-phase current supply, than the coil will arise rotary field. Because there is a rotating field in the stator coil will cause the rotor to rotate. This happens because of the induction magnet rotor synchronous with the rotational speed and rotational speed of the stator. This can be overcome by intelligent control based Artificial Intelligent (AI). In this study, designed the model of the induction motor speed control using multiple controls, including auto tuning Matlab  PID  control,  PID  with  Particle  Optimizations  Swarm  (PSO)  and  combining  methods  Neural  Adaptive  Fuzzy Inference System (ANFIS) to the PSO on a Proportional Integral Derivative (PID) controller. The results of the performance of the model of induction motor speed control using the Hybrid ANFIS-PID-PSO obtained settling time and overshoot are better than the PID Auto tuning Matlab, PID-ZN (Ziegler Nichols), as well as PID-PSO. From the results of running the program Simulink obtained the smallest overshoot value obtained in Hybrid controller ANFIS-PID-PSO at 1.007 and fastest settling time also on ANFIS controller-PID-PSO with a time of 0.73 seconds. Thus the hybrid controller models ANFIS-PID- PSO is best used in this study and can be applied into real form.