Novel approach for estimation of light-emitting diode lamp parameters based on hybrid metaheuristic algorithms - Micev, Mihailo; Ćalasan, Martin; Tokić, Amir (Journal of computational electronics, 2026)
This paper presents the parameter estimation of two types of light-emitting diode (LED) lamps based on experimentally recorded input current waveforms. The estimation process is formulated as an optimization problem and solved using metaheuristic algorithms. Initially, four different metaheuristics—Lyrebird optimization algorithm, Pelican optimization algorithm, Pufferfish optimization algorithm, and Red Kite optimization algorithm (ROA)—are applied to estimate the unknown parameters of the LED lamps. After identifying ROA as the most suitable algorithm, two hybrid variants are developed to further improve convergence speed and estimation accuracy. The performance of the proposed hybrid algorithms is evaluated and compared in terms of accuracy and convergence speed. Moreover, robustness analysis is conducted to assess performance under different operating conditions. The results demonstrate that the hybrid ROA variants outperform the standard algorithm, providing more precise parameter values and faster convergence for both LED lamp models. Finally, harmonic analysis confirms the accuracy of the estimation when using the proposed hybrid metaheuristic algorithms.