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

The result's identifiers

  • Result code in 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>

  • Alternative codes found

    RIV/61989100:27730/25:10257459

  • Result on the web

    <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>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20200 - Electrical engineering, Electronic engineering, Information engineering

Result continuities

  • Project

    <a href="/en/project/TN02000025" target="_blank" >TN02000025: National Centre for Energy II</a><br>

  • Continuities

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

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Scientific Reports

  • ISSN

    2045-2322

  • e-ISSN

    2045-2322

  • Volume of the periodical

    15

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    17

  • Pages from-to

    nestránkováno

  • UT code for WoS article

    001439741800012

  • EID of the result in the Scopus database