Balancing a Practical Inverted Pendulum Model Employing Novel Meta-Heuristic Optimization-based Fuzzy Logic Controllers

This paper concentrates on proposing a newly effective control approach to ensure the balance of an inverted pendulum (IP) system consisting of a free-rotational rod and a small cart. The novel idea is to create an effective integration between a PD-like fuzzy logic architecture and a modified genetic algorithm (mGA). The mGA is executed with an appropriately fast optimization as an initial phase in dealing with optimizing scaling factors of the fuzzy logic controller. There are totally six meaningful scaling factors corresponding to two fuzzy logic controllers applied in the balance control system of the IP. These six scaling coefficients are highly significant to strongly affect control quality of the system applying such a PD-like fuzzy logic control methodology. Excellent results obtained in terms of numerical simulations compared with those of both the conventional PID and existed fuzzy logic counterparts as well as practical experiments implemented in a real IP topology verify the promising applicability of the new control methodology proposed in this study.

@article{Mai-Phuong2022,
  title     = {Balancing a Practical Inverted Pendulum Model Employing Novel Meta-Heuristic Optimization-based Fuzzy Logic Controllers},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {4},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Dao-Thi Mai-Phuong and Pham Van-Hung and Nguyen Ngoc-Khoat and Pham Van-Minh},
  doi       = {10.14569/IJACSA.2022.0130464},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130464}
}