Line Follower Robot Optimization based Fuzzy Logic Controller Using Membership Function Tuning

  • Authors

    • Supriadi Supriadi
    • Ansar Rizal
    • Didi Susilo Budi Utomo
    • Agusma Wajiansyah
    2018-03-05
    https://doi.org/10.14419/ijet.v7i2.2.12747
  • Fuzzy Logic Controller, Line Follower Robot, Mamdani.

  • The study was aimed to measure the performance of Fuzzy Logic Controller (FLC) on Line Follower Robot (LFR). FLC output is a deviation value of Pulse Width Modulation (PWM) to determine the rotational speed of the left and the right wheel. As input variables are current and previous line sensors. Tuning was applied to input and output variables in each membership function (MF) to conduct the best performance. This study used triangular membership function that consists of three MF. Mamdani Fuzzy Inference System (FIS) is used using nine rules. The result obtains that after MF tuning, the performance of the LFR settling time is 0.63s faster compare to that without tuning.

     

     

  • References

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  • How to Cite

    Supriadi, S., Rizal, A., Susilo Budi Utomo, D., & Wajiansyah, A. (2018). Line Follower Robot Optimization based Fuzzy Logic Controller Using Membership Function Tuning. International Journal of Engineering & Technology, 7(2.2), 112-116. https://doi.org/10.14419/ijet.v7i2.2.12747