Performance Enhancement of Fuzzy Logic Controllers via Novel GWO-ABC-Based Optimization

International Journal of Electrical and Electronics Engineering

© 2025 by SSRG - IJEEE Journal

Volume 12 Issue 4

Year of Publication : 2025

Authors : Ngoc-Khoat Nguyen, Thai-Duong Le, Duy-Thuan Vu, Tien-Dung Nguyen, Thi-Duyen Bui, Thi-Mai-Phuong Dao

10.14445/23488379/IJEEE-V12I4P116

How to Cite?

Ngoc-Khoat Nguyen, Thai-Duong Le, Duy-Thuan Vu, Tien-Dung Nguyen, Thi-Duyen Bui, Thi-Mai-Phuong Dao, "Performance Enhancement of Fuzzy Logic Controllers via Novel GWO-ABC-Based Optimization," SSRG International Journal of Electrical and Electronics Engineering, vol. 12,  no. 4, pp. 222-230, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I4P116

Abstract:

Achieving an optimal balance between convergence speed and solution quality remains a critical challenge in complex optimization problems. This work proposes an enhanced hybrid metaheuristic that synergistically combines a typical Grey Wolf Optimization (GWO) algorithm together with an Artificial Bee Colony (ABC) mechanism. The key innovation lies in utilizing GWO's exploratory strength to generate an advantageous initial food source distribution for the ABC mechanism, leading to accelerated convergence and improved solution quality. To evaluate the algorithm's performance, it is applied to the parameter tuning of a Fuzzy Logic Controller (FLC) for an inverted pendulum on the cart system. Comparative performance evaluations, executed via MATLAB/Simulink simulations, demonstrate that the developed hybrid algorithm significantly surpasses the capabilities of standard ABC and existing GWO-ABC hybrid implementations. This highlights the proposed method's effectiveness in addressing a broad spectrum of optimization tasks.

Keywords:

Inverted pendulum, Fuzzy Logic Control, Grey Wolf Optimizer, Artificial Bee Colony, Balance control.

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