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A novel pressure control method for nonlinear shell-and-tube steam condenser system via electric eel foraging optimizer

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10257459" target="_blank" >RIV/61989100:27240/25:10257459 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/61989100:27730/25:10257459

  • Výsledek na webu

    <a href="https://www.nature.com/articles/s41598-025-92576-7" target="_blank" >https://www.nature.com/articles/s41598-025-92576-7</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1038/s41598-025-92576-7" target="_blank" >10.1038/s41598-025-92576-7</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    A novel pressure control method for nonlinear shell-and-tube steam condenser system via electric eel foraging optimizer

  • Popis výsledku v původním jazyce

    Precise pressure control in shell-and-tube steam condensers is crucial for ensuring efficiency in thermal power plants. However, traditional controllers (PI, PD, PID) struggle with nonlinearities and external disturbances, while classical tuning methods (Ziegler-Nichols, and Cohen-Coon) fail to provide optimal parameter selection. These challenges lead to slow response, high overshoot, and poor steady-state performance. To address these limitations, this study proposes a cascaded PI-PDN control strategy optimized using the electric eel foraging optimizer (EEFO). EEFO, inspired by the prey-seeking behavior of electric eels, efficiently tunes controller parameters, ensuring improved stability and precision. A comparative analysis against recent metaheuristic algorithms (SMA, GEO, KMA, QIO) demonstrates superior performance of EEFO in regulating condenser pressure. Additionally, validation against documented studies (CSA-based FOPID, RIME-based FOPID, GWO-based PI, GA-based PI) highlights its advantages over existing methods. Simulation results confirm that EEFO reduces settling time by 22.7%, overshoot by 78.7%, steady-state error by three orders of magnitude, and ITAE by 81.2% compared to metaheuristic based methods. The EEFO-based controller achieves faster convergence, enhanced robustness to disturbances, and precise tracking, making it a highly effective solution for real-world applications. These findings contribute to optimization-based control strategies in thermal power plants and open pathways for further bio-inspired control innovations.

  • Název v anglickém jazyce

    A novel pressure control method for nonlinear shell-and-tube steam condenser system via electric eel foraging optimizer

  • Popis výsledku anglicky

    Precise pressure control in shell-and-tube steam condensers is crucial for ensuring efficiency in thermal power plants. However, traditional controllers (PI, PD, PID) struggle with nonlinearities and external disturbances, while classical tuning methods (Ziegler-Nichols, and Cohen-Coon) fail to provide optimal parameter selection. These challenges lead to slow response, high overshoot, and poor steady-state performance. To address these limitations, this study proposes a cascaded PI-PDN control strategy optimized using the electric eel foraging optimizer (EEFO). EEFO, inspired by the prey-seeking behavior of electric eels, efficiently tunes controller parameters, ensuring improved stability and precision. A comparative analysis against recent metaheuristic algorithms (SMA, GEO, KMA, QIO) demonstrates superior performance of EEFO in regulating condenser pressure. Additionally, validation against documented studies (CSA-based FOPID, RIME-based FOPID, GWO-based PI, GA-based PI) highlights its advantages over existing methods. Simulation results confirm that EEFO reduces settling time by 22.7%, overshoot by 78.7%, steady-state error by three orders of magnitude, and ITAE by 81.2% compared to metaheuristic based methods. The EEFO-based controller achieves faster convergence, enhanced robustness to disturbances, and precise tracking, making it a highly effective solution for real-world applications. These findings contribute to optimization-based control strategies in thermal power plants and open pathways for further bio-inspired control innovations.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    20200 - Electrical engineering, Electronic engineering, Information engineering

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/TN02000025" target="_blank" >TN02000025: Národní centrum pro energetiku II</a><br>

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Ostatní

  • Rok uplatnění

    2025

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Scientific Reports

  • ISSN

    2045-2322

  • e-ISSN

    2045-2322

  • Svazek periodika

    15

  • Číslo periodika v rámci svazku

    1

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    17

  • Strana od-do

    nestránkováno

  • Kód UT WoS článku

    001439741800012

  • EID výsledku v databázi Scopus