Design of intelligent fuzzy fractional-order PID controller for pressure control application

N. Kanagaraj, Mujahed Al-Dhaifalla, K. S. Nisar

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

10 Scopus citations

Abstract

A fuzzy fractional-order proportional integral derivative (FFOPID) control scheme is proposed. In the recent years, the application of fractional calculus has been applied in science and engineering fields and proved to be a better. However, the use of fuzzy with fractional order control strategy for real-time control has not been studied greatly. In this proposed work an intelligent fuzzy fractional-order PID controller is designed and its performance is studied with a novel pressure regulating system model. To emphasize the advantages of proposed control scheme, the controller performances are investigated under load disturbances and changes in set-point conditions. A comparative study is also made with fractional order proportional integral derivative (FOPID) and classical PID control schemes. From the simulation results, the proposed control scheme outperforms other types of control scheme.

Original languageEnglish
Title of host publication2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages525-530
Number of pages6
ISBN (Electronic)9781509061068
DOIs
StatePublished - 2 Jul 2017
Event2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017 - Kannur, India
Duration: 6 Jul 20177 Jul 2017

Publication series

Name2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017
Volume2018-January

Conference

Conference2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017
Country/TerritoryIndia
CityKannur
Period6/07/177/07/17

Keywords

  • Fractional order controller
  • Fuzzy logic control
  • PID controller
  • Pressure control
  • Pressure system identification

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