OPTIMASI KECEPATAN MOTOR DC MENGGUNAKAN HYBRID ANFIS-PID-FA CONTROLLER

Buyung Imawan, Suprima Suprima, Yanuangga Gala Hartlambang, Muhlasin Muhlasin

Sari


Nonlinearity  of  the  DC  motor  will  make  the  application  to  control  the  speed automatically. Unfortunately, non-linear dynamic model of a DC motor has limitations on the design of a series of close-loop feedback controllers. Non-linear characteristics of DC motors such as friction and saturation can degrade the performance of conventional controls. This can be overcome by intelligent control based Artificial Intelligent (AI). In this study, designed the model of DC motor speed control using some sort of control, namely autotuning  matlab PID control, PID with Firefly Algorithms (FA) and combining methods Neural Adaptive Fuzzy Inference System with Firefly Algorithms on Proportional Integral Derivative controller. The results of the performance of the model DC motor speed control using the Hybrid ANFIS- PID-FA found to have a settling time and overshoot are better than the PID Autotuning  Matlab, PID-ZN (Ziegler Nichols PID), or PID-FA. Of running several models of regulation (PID control-ZN, PID Autotuning  Matlab, PID-FA, ANFIS-PID-FA) obtained settling time later than 5.00 seconds on the model without a controller, Overshoot highest 1.492 on PID- ZN, while Overshoot smallest 1.015 and the fastest settling time 0.285 seconds on ANFIS- PID-FA. This shows that the hybrid ANFIS-PID-controller FA is the best in this study.

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