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PSO Tuning of Fuzzy Multi-model Sliding Mode Controller for Thermal Process

  • Universidad San Francisco de Quito
  • Universidad Católica del Norte

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

Abstract

This study proposes an advanced control strategy that combines Fuzzy Multi-Model Control (FMMC) and Sliding Mode Control (SMC) to improve the regulation of chemical processes characterized by nonlinear dynamics. The approach is based on a Takagi–Sugeno (TS) fuzzy model, where each rule represents a local linear subsystem, allowing for smooth transitions between operating regions and thereby enhancing the overall control system’s robustness. By integrating the adaptive nature of fuzzy modeling with SMC, the proposed controller achieves superior performance in both transient and steady-state responses when compared to conventional methods, demonstrating its effectiveness for complex industrial processes.

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
Pages86-100
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

  • Fuzzy Multi-model
  • PSO
  • Sliding Mode Control
  • Thermal Process
  • time Delay

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