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Design of Fuzzy Logic-Based PID Controller for Heat Exchanger Used in Chemical Industry

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New Paradigm in Decision Science and Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1005))

Abstract

In industries, the use of heat exchanger is badly necessary to transfer heat through fluid. For such purpose, control of temperature has a great role, so that PID controller is used vastly. This paper basically focuses upon the feed-forward–feedback control strategy involved along with the PID controller. This control strategy cancels the effect of the measured disturbances and load changes in the system. The use of fuzzy controller tuning of PID controller makes the system intelligent and robust. The simulation results endorse the effectiveness of fuzzy controller-based tuning along with the feed-forward–feedback control strategy.

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Author information

Authors and Affiliations

  1. Department of Electronics and Instrumentation Engineering, College of Engineering and Technology, Bhubaneswar, India

    Mohan Debarchan Mohanty

  2. Department of Electronics and Communication Engineering, ITER, Siksha ‘O’ Anusandhan Deemed University, Bhubaneswar, Odisha, India

    Mihir Narayan Mohanty

Authors
  1. Mohan Debarchan Mohanty
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  2. Mihir Narayan Mohanty
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Corresponding author

Correspondence to Mihir Narayan Mohanty .

Editor information

Editors and Affiliations

  1. Siksha ‘O’ Anusandhan University, Bhubaneswar, India

    Srikanta Patnaik

  2. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Andrew W. H. Ip

  3. Department of Business Systems and Analytics, La Salle University, Philadelphia, PA, USA

    Madjid Tavana

  4. Victoria Business School, School of Management, Victoria University of Wellington, Wellington, New Zealand

    Vipul Jain

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Mohanty, M.D., Mohanty, M.N. (2020). Design of Fuzzy Logic-Based PID Controller for Heat Exchanger Used in Chemical Industry. In: Patnaik, S., Ip, A., Tavana, M., Jain, V. (eds) New Paradigm in Decision Science and Management. Advances in Intelligent Systems and Computing, vol 1005. Springer, Singapore. https://doi.org/10.1007/978-981-13-9330-3_37

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