IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v27y2025i5d10.1007_s10668-023-04363-x.html
   My bibliography  Save this article

Design of supervisory fuzzy control for enhanced energy saving in a sequencing batch reactor-based wastewater treatment plant

Author

Listed:
  • Indranil Dey

    (National Institute of Technology)

  • Sridhar Pilli

    (National Institute of Technology)

  • Seshagiri Rao Ambati

    (National Institute of Technology
    Indian Institute of Petroleum & Energy (IIPE))

Abstract

Humankind has been grappling with wastewater treatment for centuries. To ensure optimal operation and control of a wastewater treatment plant (WWTP), suitable advanced control strategies are required as they are inherently nonlinear in nature and subjected to different influent conditions. This paper proposes a novel supervisory control scheme for sequencing batch reactor (SBR)-based WWTP. It integrates hierarchical fuzzy control, based on ammonia and nitrate observations, in the presence of lower-level proportional integral (PI) and fractional-order PI (FPI) controllers, with the dual goal of aeration cost reduction and effluent quality enhancement. A modified ASM2d (activated sludge model No. 2d) framework is used as a model for SBR. In the hierarchical control system, variable dissolved oxygen (DO) trajectories are generated by the supervisory fuzzy logic controller and passed to the lower-level controller, according to ammonia and nitrate profiles within SBR. It is crucial to adjust this element properly in order to maximize wastewater treatment efficiency and reduce plant costs, especially for the aeration system. A notable aspect of nitrate-based hierarchical control scheme is to curtail the fresh oxygen use since nitrate (SNO), a product of nitrification, is utilized for limiting aeration costs. Six distinct control techniques are implemented of which PI and FPI controllers for control of DO at the lower level. Four types of hierarchical ammonia and nitrate-based controllers employing intelligent fuzzy control are deployed. Addition of fuzzy controller contributes to an airflow reduction of 40.08% for ammonia control and 31.58% for nitrate control strategies. This study highlights the superiority of the ammonia-based control strategy, particularly coupled with lower-level FPI controller, based on its ability to minimize airflow without affecting effluent quality. These findings offer helpful insights for advancing the field of wastewater treatment, improving efficiency, and promoting cost-effective and sustainable practices in SBR.

Suggested Citation

  • Indranil Dey & Sridhar Pilli & Seshagiri Rao Ambati, 2025. "Design of supervisory fuzzy control for enhanced energy saving in a sequencing batch reactor-based wastewater treatment plant," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(5), pages 11391-11418, May.
    • Handle: RePEc:spr:endesu:v:27:y:2025:i:5:d:10.1007_s10668-023-04363-x
    DOI: 10.1007/s10668-023-04363-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-023-04363-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10668-023-04363-x?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:spr:endesu:v:27:y:2025:i:5:d:10.1007_s10668-023-04363-x. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.