Full-Scale Output Adjustment of CSTR by Feedforward and Feedback Controllers

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

Abstract

Artificial bee colony (ABC) and particle swarm optimization (PSO) heuristic controlling methods are developed and incorporated in the feedforward and feedback controllers of the continuous stirred tank reactor (CSTR) model. The output control is able to track the input reference signal and has the capability of full-scale adjustment from 0% to 100% based on the demand. When the tracking control constant is adjusted to 0%/100%, the output signal is operated at 0%/100% by ignoring the open/closed-loop feedforward/feedback controller and relaying on the closed/open-loop feedback/feedforward controller only. The parameter estimate has a wider scope of pole placement option in compared to the existing RLS design. In the simulation, the proposed heuristic controlling methods were able to reach up to 0.8 pole placement, whereas the existing RLS controller was limited up to 0.5.

Original languageEnglish
Title of host publication8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages226-231
Number of pages6
ISBN (Electronic)9798350362138
DOIs
StatePublished - 2024
Event8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024 - Milano, Italy
Duration: 18 Sep 202420 Sep 2024

Publication series

Name8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024 - Proceeding

Conference

Conference8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024
Country/TerritoryItaly
CityMilano
Period18/09/2420/09/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • artificial bee colony
  • continuous stirred tank reactor
  • full-scale output control
  • particle swarm optimization
  • tracking

ASJC Scopus subject areas

  • Media Technology
  • Control and Optimization
  • Modeling and Simulation
  • Artificial Intelligence
  • Computer Science Applications
  • Signal Processing
  • Energy Engineering and Power Technology

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