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Design of a Self-Tuning PID Controller for a Temperature Control System Using Fuzzy Logic

  • Md Tauhidul Islam
  • , Ariful Islam
  • , Rahul Kumar*
  • , Ghulam E. Mustafa Abro
  • , Sourav Majumdar
  • , Vipin Kumar Oad
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Temperature plays a significant role in industrial realm, especially in metallurgy and chemical industries. As maintaining optimal conditions in manufacturing can make a huge difference to its profitability and efficiency. Without providing a proper temperature control, the entire production lines can fall apart. Every product needs to be manufactured in an individual and specific conditions. If the temperature is too high or too low then it can affect the output product, potentially it may ruin completely and leads to wasting of raw materials. To maintain the stability of temperature requiring in any situation a temperature control system is needed. Typically classical conventional PID controllers are being used but these controllers have some lack of efficiency in controlling. These controllers exhibit higher overshoot, long rise time and settling time. Self- tuning Fuzzy PID controllers are more efficient than those classical PID control- lers. In this paper we proposed a design of Fuzzy Logic based self-tuning PID controller to reduce overshoot and conquer long rise time and settling time. This design provides more suitable and effective control to the temperature control system in industries.

Original languageEnglish
Title of host publicationInternational Conference on Artificial Intelligence for Smart Community - AISC 2020
EditorsRosdiazli Ibrahim, Ramani Kannan, Nursyarizal Mohd Nor, K. Porkumaran, S. Prabakar
PublisherSpringer Science and Business Media Deutschland GmbH
Pages643-649
Number of pages7
ISBN (Print)9789811621826
DOIs
StatePublished - 2022
Externally publishedYes
Event1st International Conference on Artificial Intelligence for Smart Community, AISC 2020 - Virtual, Online
Duration: 17 Dec 202018 Dec 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume758
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference1st International Conference on Artificial Intelligence for Smart Community, AISC 2020
CityVirtual, Online
Period17/12/2018/12/20

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Conventional PID
  • First self-tuning PID controller
  • Fuzzy interference system (FIS)
  • MATLAB
  • Temperature

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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