Implementation of Mamdani Fuzzy Logic Control System on DC Motor Speed Controller

Basilio Mendonca Freitas, Mochammad Rameli, Rusdhianto EAK


Abstract— Drive system is an important role important role in industrial processes, especially in electrical control. Maintaining a DC motor speed is a control system task that requires several method. Generally, set-point is defined as point of demand, and its comparation against process value (current speed) resulted in error. Both error and delta-error are two parameters required to the control system to determine system behavior in correction action. Such system of controller is a useful component to suppress the error signal so that the desired performance can be obtained. This research designs system of DC motor rotation speed control using Arduino Uno microcontroller to meet control specification on laboratory scale, implementing control application and Fuzzy Control System as control system algorithm.

Because of its ability to be easily modeled using human intuitive, adaptive, does not require complex mathematical equations, not limited to linear or constant systems, and easily adapted to human input, Mamdani Fuzzy Logic Control System is used.

Full Text:



Azadi, Sassan, & Mosa, Nouri. 2012. Utilizing Azadi Controller to Stabilize the Speed of a DC Motor. Proceedings of the 2012 International Conference on Advanced Mechatronic Systems, Tokyo, Japan. p. 269-274.

Farid, Ali Moltajaei, & Barakati, S. Masoud. 2014. DC Motor Neuro-Fuzzy Controller Using PSO Identification. The 22nd Iranian Conference on Electrical Engineering. p. 1162-1167.

Muslim, M. Aziz, Minggu, Desyderius, Saputra, Jeki, Hasanah, Rini Nur. 2015. Comparison Analysis Between Fuzzy and Fuzzified-PID Methods on Gun-Barrel Motion Control. ARPN Journal of Engineering and Applied Sciences. Asian Research Publishing Network. Retrieved 2016-11-03.

Kuo, Benjamin C & Golnaraghi M F. 2003. Automatic Control Systems (Eighth ed.). NY: Wiley. p. §7.3 p. 236–237.

Johnson, H. and Graham, 1993. M. High-Speed Digital Design: A Handbook of Black Magic. pp. 88–90.

Cherry, E. M.; Hooper, D. E. 1968. Amplifying Devices and Low-pass Amplifier Design, New York–London–Sidney: John Wiley & Sons, pp. xxxii+1036.

Elmore, William C. 1948. The Transient Response of Damped Linear Networks with Particular Regard to Wideband Amplifiers, Journal of Applied Physics, pp. 55–63.

Levine, William S. 1996. The Control Handbook, Boca Raton, FL: CRC Press, pp. xvi+1548.

Levine, William S. 2011., The Control Handbook: Control Systems Fundamentals (2nd ed.), Boca Raton, FL: CRC Press, pp. xx+766.

Millman, Jacob; Taub, Herbert. 1965. Pulse, Digital and Switching Waveforms. New York–St. Louis–San Francisco–Toronto–London–Sydney: McGraw-Hill, pp. xiv+958.

National Communication Systems, Technology and Standards Division. 1997. Federal Standard 1037C. Telecommunications: Glossary of Telecommunications Terms, FSC TELE, FED–STD–1037, Washington: General Service Administration Information Technology Service, p. 488.

Nise, Norman S. 2011. Control Systems Engineering (6th ed.), New York: John Wiley & Sons, pp. xviii+928.

Novák, V., Perfilieva, I. and Močkoř, J. 1999. Mathematical principles of fuzzy logic Dodrecht: Kluwer Academic.

Ahlawat, Nishant, Ashu Gautam, and Nidhi Sharma. 2014. Use of Logic Gates to Make Edge Avoider Robot. International Journal of Information & Computation Technology. pp. 630

Fuzzy Logic. Stanford Encyclopedia of Philosophy. Bryant University. 2006-07-23. Retrieved 2008-09-30.

Zadeh, L.A. 1965. Fuzzy Sets. Information and Control. pp. 338–353.

Pelletier, Francis Jeffry. 2000. Review of Metamathematics of Fuzzy Logics. The Bulletin of Symbolic Logic. pp. 342–346.

Arduino - Introduction. Retrieved 2016-08-12.

David Kushner. 2011. The Making of Arduino. IEEE Spectrum.

Justin Lahart. 2009. Taking an Open-Source Approach to Hardware. The Wall Street Journal. Retrieved 2014-09-07


  • There are currently no refbacks.