Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)

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Adaptive Neuro-Fuzzy Inference System with Dragonfly Optimization: An Advanced Control Solution for Shell and Tube Heat Exchangers

Authors
P. Karunakaran1, *, S. Prakash1
1Department of Electrical and Electronics Engineering, Bharath Institute of Higher Education and Research, Chennai, Tamil Nādu, India
*Corresponding author. Email: pkarunaas@gmail.com
Corresponding Author
P. Karunakaran
Available Online 24 April 2026.
DOI
10.2991/978-94-6239-654-8_7How to use a DOI?
Keywords
Heat Exchanger; Control; Neuro; Fuzzy and Dragonfly
Abstract

This study introduces a sophisticated control method for Shell and Tube Heat Exchangers (STHEs) by combining an Internal Model Control (IMC) with Adaptive Neuro-Fuzzy Inference System (ANFIS) models enhanced by the Dragonfly Algorithm. This innovative technique utilizes ANFIS for both the forward and inverse modeling of the heat exchanger, effectively capturing the intricate, nonlinear dynamics of the system. The Dragonfly Algorithm is utilized to optimize the ANFIS parameters and enhance the accuracy and adaptability of the model. In the IMC framework, the forward ANFIS model predicts the process output based on the control inputs, whereas the inverse ANFIS model determines the necessary control actions to achieve the desired temperature. This integration allows for precise and real-time adjustment of control actions, thereby improving the temperature regulation and overall system performance. The combined use of the IMC and optimized ANFIS models offers a robust solution for effective temperature control in STHE applications.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)
Series
Advances in Engineering Research
Publication Date
24 April 2026
ISBN
978-94-6239-654-8
ISSN
2352-5401
DOI
10.2991/978-94-6239-654-8_7How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - P. Karunakaran
AU  - S. Prakash
PY  - 2026
DA  - 2026/04/24
TI  - Adaptive Neuro-Fuzzy Inference System with Dragonfly Optimization: An Advanced Control Solution for Shell and Tube Heat Exchangers
BT  - Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)
PB  - Atlantis Press
SP  - 67
EP  - 78
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-654-8_7
DO  - 10.2991/978-94-6239-654-8_7
ID  - Karunakaran2026
ER  -