Particle Swarm Optimization Based Closed Loop Control for a DC-DC Buck Converter for Enhanced Dynamic Performance and Robustness

O. L. Avworo; B. O. Ogbonna

O. L. Avworo Department of Electrical and Electronics Engineering, Federal University of Petroleum Resources, Effurun, Nigeria
B. O. Ogbonna Department of Electrical and Electronics Engineering, University of Port Harcourt, Port Harcourt, Nigeria

Keywords: Buck converter, closed loop control, Particle Swarm Optimization (PSO), PID tuning, metaheuristic optimization, power electronics, dynamic response, robustness

Abstract

DC-DC buck converters are widely used in modern power electronic applications, including renewable energy systems and IoT devices. Their nonlinear behavior under varying load conditions requires effective closed-loop control. In most cases, the proportional-integral-derivative (PID) controllers are used with the converter, their performance often deteriorates when the operating conditions change or disturbances occur. This paper will present a systematic offline Particle Swarm Optimization (PSO) approach for tuning a voltage-mode PID controller for a buck converter operating in continuous conduction mode (CCM). An averaged state-space model that includes parasitic resistances is developed to improve modelling accuracy and stability. The PSO algorithm helps to optimize the proportional, integral and derivative gains by minimizing a composite time-weighted integral of absolute error (ITAE) objective function. MATLAB/Simulink simulations will show that the PSO-tuned controller delivers a faster transient response, lower overshoot, shorter settling time and better disturbance rejection than the Ziegler-Nichols, genetic algorithm and manually tuned controllers. Its superiority is further verified under load variations and input voltage fluctuations. The proposed method offers a practical and reproducible tuning procedure, supported by convergence analysis and implementation guidelines, demonstrating that PSO is an effective and computationally efficient technique for optimizing power converter control.

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