Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm

•A modified density-decreasing factor in the AOA provides balance exploration and exploitation phases.•A safe update mechanism is proposed to solve the issue of local optima entrapment in the original AOA.•IAOA provides better accuracy of continuous-time Hammerstein model than the original AOA.•Data...

Celý popis

Podrobná bibliografia

Vydané v:	Results in engineering Ročník 24; s. 103357
Hlavní autori:	Islam, Muhammad Shafiqul, Ahmad, Mohd Ashraf
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.12.2024 Elsevier
Predmet:	Archimedes optimization algorithm Data-driven control with missing data Data-driven Hammerstein modeling Electrical-mechanical positioning system Metaheuristics algorithms Twin rotor system Electrical-mechanical positioning system Metaheuristics algorithms Data-driven Hammerstein modeling Data-driven control with missing data Archimedes optimization algorithm Twin rotor system
ISSN:	2590-1230, 2590-1230
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!