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Full State Observer Versus NARX-Based as Soft Sensor for Reactor–Separator–Recycle Process Control

  • Universidad San Francisco de Quito
  • Universidad Católica del Norte

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

Abstract

This article describes the design of a control system for a common industrial process, the Reactor-Separator-Recycler (RSR), and the development of two estimators: a full-state observer and an artificial neural network, to estimate the concentration at the output of the Continuous Stirred Tank Reactor (CSTR) in the RSR process. For the controller design, empirical approximate models are obtained from the reaction curve via identification procedures. The estimated concentration is used to close a control loop for the CSTR. Temperature perturbation tests and initial concentration estimations at the mixing point are performed. The results show the efficiency of the neural network compared to the full-state observer.

Original languageEnglish
Title of host publicationApplications of Computational Intelligence - 8th IEEE Colombian Conference, ColCACI 2025, Revised Selected Papers
EditorsAlvaro David Orjuela-Cañón, Jesus A Lopez, Oscar J Suarez
PublisherSpringer Science and Business Media Deutschland GmbH
Pages118-132
Number of pages15
ISBN (Print)9783032208996
DOIs
StatePublished - 2026
Event8th IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2025 - Armenia, Colombia
Duration: 27 Aug 202529 Aug 2025

Publication series

NameCommunications in Computer and Information Science
Volume2846 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference8th IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2025
Country/TerritoryColombia
CityArmenia
Period27/08/2529/08/25

Keywords

  • Full State Observer
  • NARX- network
  • Soft Sensor

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