IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0309211.html
   My bibliography  Save this article

Nonlinear FOPID controller design for pressure regulation of steam condenser via improved metaheuristic algorithm

Author

Listed:
  • Sarah A Alzakari
  • Davut Izci
  • Serdar Ekinci
  • Amel Ali Alhussan
  • Fatma A Hashim

Abstract

Shell and tube heat exchangers are pivotal for efficient heat transfer in various industrial processes. Effective control of these structures is essential for optimizing energy usage and ensuring industrial system reliability. In this regard, this study focuses on adopting a fractional-order proportional-integral-derivative (FOPID) controller for efficient control of shell and tube heat exchanger. The novelty of this work lies in the utilization of an enhanced version of cooperation search algorithm (CSA) for FOPID controller tuning, offering a novel approach to optimization. The enhanced optimizer (en-CSA) integrates a control randomization operator, linear transfer function, and adaptive p-best mutation integrated with original CSA. Through rigorous testing on CEC2020 benchmark functions, en-CSA demonstrates robust performance, surpassing other optimization algorithms. Specifically, en-CSA achieves an average convergence rate improvement of 23% and an enhancement in solution accuracy by 17% compared to standard CSAs. Subsequently, en-CSA is applied to optimize the FOPID controller for steam condenser pressure regulation, a crucial aspect of heat exchanger operation. Nonlinear comparative analysis with contemporary optimization algorithms confirms en-CSA’s superiority, achieving up to 11% faster settling time and up to 55% reduced overshooting. Additionally, en-CSA improves the steady-state error by 8% and enhances the overall stability margin by 12%.

Suggested Citation

  • Sarah A Alzakari & Davut Izci & Serdar Ekinci & Amel Ali Alhussan & Fatma A Hashim, 2024. "Nonlinear FOPID controller design for pressure regulation of steam condenser via improved metaheuristic algorithm," PLOS ONE, Public Library of Science, vol. 19(9), pages 1-33, September.
  • Handle: RePEc:plo:pone00:0309211
    DOI: 10.1371/journal.pone.0309211
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0309211
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0309211&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0309211?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Prajapati, Parth & Raja, Bansi D. & Savaliya, Hepin & Patel, Vivek & Jouhara, Hussam, 2024. "Thermodynamic evaluation of shell and tube heat exchanger through advanced exergy analysis," Energy, Elsevier, vol. 292(C).
    2. Adeel Ahmad Jamil & Wen Fu Tu & Syed Wajhat Ali & Yacine Terriche & Josep M. Guerrero, 2022. "Fractional-Order PID Controllers for Temperature Control: A Review," Energies, MDPI, vol. 15(10), pages 1-28, May.
    3. Shu-Xia Li & Jie-Sheng Wang, 2015. "Dynamic Modeling of Steam Condenser and Design of PI Controller Based on Grey Wolf Optimizer," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-9, December.
    4. Oravec, Juraj & Bakošová, Monika & Trafczynski, Marian & Vasičkaninová, Anna & Mészáros, Alajos & Markowski, Mariusz, 2018. "Robust model predictive control and PID control of shell-and-tube heat exchangers," Energy, Elsevier, vol. 159(C), pages 1-10.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Çetin, Gürcan & Özkaraca, Osman & Keçebaş, Ali, 2021. "Development of PID based control strategy in maximum exergy efficiency of a geothermal power plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    2. Xin, Feng & Xu, Bowen & Dai, Dongdong & Liu, Wei & Liu, Zhichun, 2024. "Evaluation of heat transfer enhancement effect at the hot/cold end of a Stirling engine using performance improvement factor," Energy, Elsevier, vol. 311(C).
    3. Jiří Jaromír Klemeš & Petar Sabev Varbanov & Paweł Ocłoń & Hon Huin Chin, 2019. "Towards Efficient and Clean Process Integration: Utilisation of Renewable Resources and Energy-Saving Technologies," Energies, MDPI, vol. 12(21), pages 1-32, October.
    4. Andrés Fernández-Miguel & Davide Settembre-Blundo & Marco Vacchi & Fernando E. García-Muiña, 2025. "Thermoeconomics Meets Business Science: Systemic Exergy Management (SYMΞX) as a New Theoretical and Flexible Framework for Sustainability," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 26(1), pages 111-139, March.
    5. Trafczynski, Marian & Markowski, Mariusz & Urbaniec, Krzysztof, 2019. "Energy saving potential of a simple control strategy for heat exchanger network operation under fouling conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 355-364.
    6. Wan, Xin & Luo, Xiong-Lin, 2020. "Economic optimization of chemical processes based on zone predictive control with redundancy variables," Energy, Elsevier, vol. 212(C).
    7. Brage Rugstad Knudsen & Hanne Kauko & Trond Andresen, 2019. "An Optimal-Control Scheme for Coordinated Surplus-Heat Exchange in Industry Clusters," Energies, MDPI, vol. 12(10), pages 1-22, May.
    8. Mingjun Li & Jiangyang Pan & Yaolai Liu & Yazhou Wang & Wenchuan Zhang & Junxing Wang, 2022. "Dam deformation forecasting using SVM-DEGWO algorithm based on phase space reconstruction," PLOS ONE, Public Library of Science, vol. 17(6), pages 1-39, June.
    9. Trafczynski, Marian & Markowski, Mariusz & Urbaniec, Krzysztof, 2023. "Energy saving and pollution reduction through optimal scheduling of cleaning actions in a heat exchanger network," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    10. Oravec, Juraj & Horváthová, Michaela & Bakošová, Monika, 2020. "Energy efficient convex-lifting-based robust control of a heat exchanger," Energy, Elsevier, vol. 201(C).
    11. Zhang, Kezhen & Zhao, Yongliang & Liu, Ming & Gao, Lin & Fu, Yue & Yan, Junjie, 2021. "Flexibility enhancement versus thermal efficiency of coal-fired power units during the condensate throttling processes," Energy, Elsevier, vol. 218(C).
    12. Seferlis, Panos & Varbanov, Petar Sabev & Papadopoulos, Athanasios I. & Chin, Hon Huin & Klemeš, Jiří Jaromír, 2021. "Sustainable design, integration, and operation for energy high-performance process systems," Energy, Elsevier, vol. 224(C).
    13. Ikram Boucetta & Djemai Naimi & Ahmed Salhi & Saleh Abujarad & Laid Zellouma, 2022. "Power System Stability Enhancement Using a Novel Hybrid Algorithm Based on the Water Cycle Moth-Flame Optimization," Energies, MDPI, vol. 15(14), pages 1-17, July.
    14. Pranta Das & Shuvra Prokash Biswas & Sudipto Mondal & Md Rabiul Islam, 2023. "Frequency Fluctuation Mitigation in a Single-Area Power System Using LQR-Based Proportional Damping Compensator," Energies, MDPI, vol. 16(12), pages 1-18, June.
    15. J. Alberto Conejero & Jonathan Franceschi & Enric Picó-Marco, 2022. "Fractional vs. Ordinary Control Systems: What Does the Fractional Derivative Provide?," Mathematics, MDPI, vol. 10(15), pages 1-18, August.
    16. Marcelo Becerra-Rozas & José Lemus-Romani & Felipe Cisternas-Caneo & Broderick Crawford & Ricardo Soto & José García, 2022. "Swarm-Inspired Computing to Solve Binary Optimization Problems: A Backward Q-Learning Binarization Scheme Selector," Mathematics, MDPI, vol. 10(24), pages 1-30, December.
    17. Salil Madhav Dubey & Hari Mohan Dubey & Surender Reddy Salkuti, 2022. "Modified Quasi-Opposition-Based Grey Wolf Optimization for Mathematical and Electrical Benchmark Problems," Energies, MDPI, vol. 15(15), pages 1-29, August.
    18. Dong, Zhe & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2020. "Multilayer perception based reinforcement learning supervisory control of energy systems with application to a nuclear steam supply system," Applied Energy, Elsevier, vol. 259(C).
    19. Wang, Wei & Xie, Xinyan & Yu, Wei & Hu, Yong & Zeng, Deliang, 2024. "Flexible heat and power load control of subcritical heating units based on energy demand-supply balance," Energy, Elsevier, vol. 313(C).
    20. Oravec, Juraj & Bakošová, Monika & Galčíková, Lenka & Slávik, Michal & Horváthová, Michaela & Mészáros, Alajos, 2019. "Soft-constrained robust model predictive control of a plate heat exchanger: Experimental analysis," Energy, Elsevier, vol. 180(C), pages 303-314.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0309211. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.