Parameter Identification In Nonlinear Systems Using Enzyme Action Optimizer
2025 Innovations in Intelligent Systems and Applications Conference, ASYU 2025, Bursa, Türkiye, 10 - 12 Eylül 2025, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/asyu67174.2025.11208416
- Basıldığı Şehir: Bursa
- Basıldığı Ülke: Türkiye
- Anahtar Kelimeler: enzyme action optimizer, Nonlinear system, parameter identification, stochastic optimization
- Bursa Uludağ Üniversitesi Adresli: Evet
Özet
This study investigates the applicability of the enzyme action optimizer (EAO), a recent bio-inspired metaheuristic algorithm, to the problem of parameter identification in nonlinear dynamical systems. Inspired by enzymatic behavior in biological systems, EAO combines adaptive local search with stochastic diversity mechanisms to maintain a balanced exploration of complex solution spaces. Although previously shown to be effective in general optimization tasks, this work represents the first application of EAO to the specific context of nonlinear system modeling. Two well-established benchmark systems (the Rössler chaotic system and a permanent magnet synchronous motor (PMSM) model) are considered due to their nonlinear and often chaotic behavior. Simulation results demonstrate that EAO can successfully identify unknown parameters with high accuracy, minimizing the mean squared error between simulated and reference outputs. When compared to other recent metaheuristic techniques, EAO consistently exhibits superior precision and robustness, offering a promising alternative for complex system identification tasks.