Archimedes Optimization Algorithm for PID Controller Design of Buck Converter

A closed-loop DC-DC buck converter is a type of power converter that uses a feedback loop to regulate the output voltage in response to changes in load or input voltage. A closed-loop DC-DC buck converter needs a PID controller to maintain its design voltage and safeguard any connected loads. PID controllers need to be fine-tuned in every different load situation to provide the best possible response time with minimum voltage error and voltage overshoot. With that, metaheuristic optimization algorithms can help to tune the PID controller. Accordingly, this paper introduces a well-known optimization algorithm, which is Archimedes optimization algorithm (AOA) for tuning the PID controller. The tuning results of AOA are compared to those of other popular optimizers, including the improved Nelder–Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). Comparative findings of statistical boxplot, error-integral performance indexes, and transient response are used to verify the PID controller’s performance. From this study, it can be concluded that the AOA optimization algorithm outperformed other algorithms in tuning the PID controller of a closed-loop DC-DC buck converter.