Akademik Veri Yönetim Sistemi
CUMHURIYET 17th INTERNATIONAL CONFERENCE ON APPLIED SCIENCES, Ankara, Türkiye, 23 Nisan 2026, ss.1-9, (Tam Metin Bildiri)
The nonlinear characteristics of
Photovoltaic (PV) systems and the switched-mode operation of the boost
converter limit the performance of conventional control methods. This study
addresses the development of a Particle Swarm Optimization (PSO) based Fuzzy
Logic Controller (FLC) to achieve a stable output voltage in PV power
conversion systems despite varying load and input voltage conditions. The
parameters of the fuzzy set membership functions (MF), which directly affect
controller performance, were dynamically optimized using the PSO algorithm. The
proposed method was evaluated on a PV boost converter system modeled in
MATLAB/Simulink under nominal operation, dynamic load, and input-voltage change
scenarios. The controller’s resistance to disturbances was analyzed under
conditions of an approximately 32% drop in input voltage and a 43% change in load. The system’s performance was analyzed against
classical tuned FLC using critical metrics such as RMSE, MAE, rise time (
), and settling
time (
). The
simulation results obtained demonstrate that PSO-BMD outperforms the classical
architecture in all scenarios. In particular, a 63% improvement in RMSE was
achieved; the rise time was reduced from 0.323 seconds to 0.03 seconds, thereby
increasing the system’s dynamic response speed by approximately 10 times.