Golden Jackal Optimization Algorithm For Superior Dynamic Performance Control Of Dc Motors Using Pid And Fopid Controllers
DOI:
https://doi.org/10.63746/njtd.v23i1.4138Keywords:
DC motor, Golden Jackal Optimization (GJO) Algorithm, PID controller, FOPID controller, ITAE, Meta-heuristics algorithmAbstract
Direct Current (DC) motors are integral to industrial drive systems due to their efficiency, controllability, and favorable speed-torque characteristics. Achieving optimal speed regulation with PID and FOPID controllers remains challenging, particularly under demanding transient and precision requirements. This study introduces a novel metaheuristic approach, the Golden Jackal Optimizer (GJO), inspired by the cooperative hunting behavior of golden jackals, for the optimal tuning of PID and FOPID controllers. The Integral Time Absolute Error (ITAE) criterion is employed to ensure superior dynamic performance. The proposed GJO-PID and GJO-FOPID controllers were rigorously benchmarked against ten advanced metaheuristic optimization algorithms, including IGWO, PSO, HHO, LHHO, and GOA, across multiple metrics, such as rise time, settling time, overshoot, bandwidth, and phase margin. Results reveal that the GJO controllers surpasses LHHO-FOPID by 6.98%, 4.10%, and 0.56%, and GOA-FOPID by 3.87%, 3.42%, and 0.2022% in faster rise time, shorter settling time, and lower overshoot, respectively. Furthermore, comprehensive sensitivity analyses under varying motor parameters confirm the robustness and reliability of the proposed method. These findings demonstrate the GJO algorithm’s ability to deliver superior transient response, stability, and performance, highlighting its potential as a highly effective and generalizable solution for advanced DC motor control in industrial applications.
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