A Novel Integration of Metaheuristic – Based Optimization Methods for Enhancing Fuzzy Logic Control Performance on Inverted Pendulum-Cart Systems
Ngoc-Khoat Nguyen, Thai-Duong Le, Duy-Trung Nguyen, Thi-Mai-Phuong Dao · Journal Européen des Systèmes Automatisés · 2025
This paper proposes a novel hybrid control strategy for improving the balance and trajectory tracking performance of a typical inverted pendulum system.The system is made up of a freely circling pendulum mounted on a horizontally mobile cart.The control objective is to stabilize the pendulum in an upright position while simultaneously guiding the cart along a desired trajectory.A hybrid optimization approach, combining an enhanced Particle Swarm Optimization (PSO) algorithm with the BA Algorithm (BA), is proposed to optimize the critical parameters of a direct fuzzy logic controller.In the initialization phase, PSO is utilized to generate a high-quality initial population.Subsequently, BA refines the optimization by tuning the scaling factors of the fuzzy controller.The direct fuzzy controller incorporates five preprocessing and postprocessing factors, which significantly impact the overall control performance.Numerical simulations and experimental results demonstrate that the proposed PSO-BA hybrid method achieves faster computation times and efficiently identifies optimal parameters, resulting in rapid and robust control responses even in large search spaces.Comparative analysis reveals that this novel approach outperforms conventional PID controllers and fuzzy controllers optimized with standard PSO-based techniques, exhibiting superior control quality and responsiveness.