Journal of Electrical Engineering and Renewable Energies Development
Volume 1, Numéro 1, Pages 1-8
2025-12-20
Identification Of Dc Motor Parameters Using The Zoa Metaheuristic Algorithmwith Comparative Study
Authors : Sebhi Abdelhadi . Megherbi Ahmed Chaouki . Dendouga Abdelhakim . Zitouni Athmane .
Abstract
In this work, the parameters of the direct current motor (DC motor) were estimated using its armature current and speed responses, employing a recent optimization algorithm known as the Zebra Optimization Algorithm (ZOA). ZOA is recognized for its high accuracy and fast convergence, as demonstrated in various recent studies. To evaluate its effectiveness, ZOA was applied to estimate the DC motor parameters and its performance was compared with two well-known algorithms: the Enhanced Opposition-Based Equilibrium Optimizer-Slim Mold Algorithm (EOSMA) and the Grey Wolf Optimizer (GWO). The results show that ZOA outperforms both EOSMA and GWO in minimizing the objective function, which reflects the estimation error of both armature current and speed. These findings confirm the superiority of ZOA in accurately identifying DC motor parameters
Keywords
DC Motor, Parameter Estimation, Zebra Optimization Algorithm (ZOA), Metaheuristic Algorithms, Grey Wolf Optimizer (GWO).
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