Evidence map›Paper›PMID 39794462›Full record

ArticleScientific reports2025

Design and optimal tuning of fractional order PID controller for paper machine headbox using jellyfish search optimizer algorithm.

Divya Nataraj, Manoharan Subramanian

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Divya NatarajDepartment of EEE, Sri Ramakrishna Engineering College, Coimbatore, Tamil Nadu, 641022, India. n.divyasri2026@gmail.com.
Manoharan SubramanianDepartment of EEE, JCT College of Engineering and Technology, Coimbatore, Tamil Nadu, 641105, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This manuscript proposes the Jellyfish Search Optimization (JSO) algorithm-based Fractional Order Proportional-Integral-Derivative (FOPID) controller tuning for a paper machine headbox. The novelty of this method lies in integrating the JSO technique for optimizing the parameters of the FOPID controller to monitor and control headbox pressure and stock level efficiently and effectively. The JSO algorithm ensures optimal tuning of controller parameters by minimizing error indices such as Integral of Squared Error (ISE), Integral of Time Absolute Error (ITAE), and Integral of Absolute Error (IAE). Simulations conducted on the MATLAB/Simulink platform demonstrate that the FOPID controller tuned using JSO achieves superior performance compared to conventional PI (Proportional-Integral) and PID (Proportional-Integral-Derivative) controllers. Specifically, the JSO-tuned FOPID controller exhibited a 25% reduction in rise time, a 30% improvement in settling time, and a 20% decrease in overshoot when compared to the PID controller. Furthermore, comparative analyses with other optimization techniques, including Moth Flame Optimization (MFO), Ant Lion Optimization (ALO), and Elephant Herding Optimization (EHO), reveal that the JSO algorithm provides higher accuracy and stability in diverse operating conditions. This study underscores the efficacy of the JSO-tuned FOPID controller as a robust solution for complex industrial applications, such as paper machine headbox systems, and highlights its potential to enhance process efficiency and control precision.

Indexed as

EHOFOPID controllerJSOMFO and ALOPaper machine head box

Identifiers

PMID39794462
PMCPMC11723960

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