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


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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Dwi Hartanto, Thomas Wahyu, Analisis

Dan Desain System Kontrol Dengan

MATLAB, Andy.Yokyakarta. 2001.

Husein Ahmad , Gagan Signh, Controlling

of D.C. Motor using Fuzzy Logic

Controller“, Conference on Advances

in Communication and Control

Systems 2013 (CAC2S 2013)

H. Shayeg, A. Safari and H. A. Shayanfar,

Multimachine Power System Stabilizer

Design Using Particle Swarm

Optimization Algorithm”, International

journal of Electrical Power and Energy

System Engineering, 2008, 226-233.

Karaman S, Ozturk I, Yalcın H, Kayacier

A, Sagdic O: Comparison of Adaptive

Neuro Fuzzy Inference System and

artificial neural networks for

estimation of oxidation parameters of

sunflower oil added with some natural

byproduct extracts, J. Sci. Food Agric.

(2012) 49 – 58

Muhammad H. Rashid, Power Electronics

Circuits, Devices, and Applications,

Prentice Hall, 2004

Sanju Saini, Arvind Kumar, Speed Control

of Separately Excited D.C Motor using

Self Tuned ANFIS Techniques, IJCST

Vol. 3, 2012, India.

Walaa M Strogy, Speed Control of DC

Motor Using PID Controller Base On

Artificial Intellegence Technique,

CoDIT’13 IEEE, 2013

Yang, X. S. (2009). "Firefly algorithms for

multimodal optimization". Stochastic

Algorithms: Foundations and

Applications, SAGA 2009. Lecture

Notes in Computer Sciences 5792.


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