Abstract

Tuning a nonlinear inverted pendulum is a complex and uncertain optimization problem. In this paper, we develop two new GWO variants by introducing a DLH (Dimension Learning-based Hunting) module and new formulas to enhance the exploitation/exploration ratio aiming to avoid local minima. A statistical analysis is carried out to compare the two proposed approaches with five GWO variants. After that, they are used to tune a PID and FSMC controller. The obtained results are promising even when compared to other approaches

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