DocumentCode :
3582234
Title :
Real-time fuzzy logic speed tracking controller for a DC motor using Arduino Due
Author :
Jayetileke, H.R. ; de Mei, W.R. ; Ratnayake, H.U.W.
Author_Institution :
Dept. of Mech. Eng., Open Univ. of Sri Lanka, Nugegoda, Sri Lanka
fYear :
2014
Firstpage :
1
Lastpage :
6
Abstract :
Designing and developing AI controllers on separately dedicated chips have many advantages. This paper reviews the development of a real-time fuzzy logic controller for speed control of a dc motor using Arduino Due board. The proposed fuzzy logic controller is based on Mamdani approach and has been tested on the aforementioned high performance microcontroller board and using MATLAB. During the real-time operation the dc motor behavior and the fuzzy controller´s response were plotted and the data were stored in MATLAB without interrupting the fuzzy logic controller. Based on these observed information, the system settling time and the rise time reduction were calculated for each input wave patent trajectories while increasing the wave frequency. It was noted that the system overshoot is negligible. Utilizing the aforementioned parameters the Arduino Due board performance was analyzed with the fuzzy logic speed control approaches of dc motors made by past researchers as mentioned above. The system response shows a satisfactory performance for this particular dc motor application when the input signal (desired output signal) frequency is less than 2 Hz, but further research is needed when identifying the optimum performance of the Arduino Due board for different fuzzy logic algorithms while increasing the desired input signal frequency.
Keywords :
DC motors; angular velocity control; control engineering computing; fuzzy control; microcontrollers; power engineering computing; AI controller; Arduino Due board; DC motor; Matlab; artificial intelligence; direct current motor; fuzzy logic controller; high performance microcontroller board; input signal frequency; input wave patent trajectory; realtime fuzzy logic speed tracking controller; rise time reduction; system settling time; Artificial intelligence; DC motors; Fuzzy logic; Mathematical model; Pragmatics; Pulse width modulation; Real-time systems; analog to digital converter; arduino due; artificial intelligence; controller; defuzzification; fuzzification; fuzzy inference system; fuzzy logic; linguistic fuzzy values; pulse width modulation; servo motor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation for Sustainability (ICIAfS), 2014 7th International Conference on
Type :
conf
DOI :
10.1109/ICIAFS.2014.7069560
Filename :
7069560
Link To Document :
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