| Issue |
ITM Web Conf.
Volume 72, 2025
III International Workshop on “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-III 2024)
|
|
|---|---|---|
| Article Number | 04002 | |
| Number of page(s) | 8 | |
| Section | Data Mining, Machine Learning and Pattern Recognition | |
| DOI | https://doi.org/10.1051/itmconf/20257204002 | |
| Published online | 13 February 2025 | |
Development of a fuzzy rule base design algorithm using a genetic algorithm and an inverted pendulum
1 Institute of Physics, FRC KSC SB RAS, st. Akademgorodok, 50, Krasnoyarsk, Russia
2 Reshetnev Siberian State University of Science and Technology, Krasnoyarsky Rabochy Av, 31, Krasnoyarsk, Russia
* Corresponding author: jeetee24@gmail.com
This paper presents the development of a fuzzy rule base construction algorithm that leverages a genetic algorithm to optimize control parameters for complex dynamic systems. The algorithm was tested on an inverted pendulum model, a classical nonlinear control problem, to identify chromosome configurations capable of stabilizing the pendulum in an upright position. Through extensive experimentation, the program successfully discovered such chromosomes that stabilized the pendulum from a variety of initial positions, including inverted (top-down) states, by forming the needed fuzzy rules base and fuzzy input and output terms. The results demonstrate the efficiency of the proposed approach in automating the design of fuzzy logic controllers using evolutionary methods.
© The Authors, published by EDP Sciences, 2025
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