Evolving granular fuzzy control : overview, case study on the chaotic Hénon map, and research outlook

Leite, Daniel (author), Palhares, Reinaldo (author), Škrjanc, Igor (author), Gomide, Fernando (author)

This paper highlights the relevance of evolving granular fuzzy systems in adaptive control and fuzzy modeling, particularly for learning in dynamic, nonstationary environments. These systems incrementally construct rule-based models—such as predictors and controllers operating in open- or closed-loop configurations—by adapting both structure and parameters from data streams. This provides a flexible and autonomous alternative to traditional parametric-adaptive approaches. We consolidate foundational concepts in fuzzy and adaptive control, positioning evolving systems as data-driven extensions of classical schemes. Key challenges are discussed, including safety-aware adaptation to drift, memory mechanisms, interpretability, and principled structural evolution. Building on these foundations, we develop a more mature formulation of the state-space evolving granular modeling and control framework (SS-EGM/SS-EGC), introducing a decay-rate–oriented treatment that advances the methodology beyond mere LMI feasibility toward online optimality. A compact case study on the chaotic Hénon map illustrates the approach: an online SS-EGM learned from data streams supports SS-EGC synthesis that stabilizes the map under bounded inputs. One-step prediction accuracy and decay-rate estimates confirm real-time viability. The framework provides a flexible basis that can be further extended in multiple directions to address the identified challenges.

• Language: English
• Keywords: evolving fuzzy systems, on-line active learning from streams, autonomous evolution of ensemble members
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FE - Faculty of Electrical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2026
• Number of pages: 13 str.
• Numbering: Vol. 190, art.114639
• PID: 20.500.12556/RUL-178119
• UDC: 681.5
• ISSN on article: 1872-9681
• DOI: 10.1016/j.asoc.2026.114639
• COBISS.SI-ID: 265060099
• Publication date in RUL: 19.01.2026

Record is a part of a journal

• Title: Applied soft computing
• Publisher: Elsevier Science
• ISSN: 1872-9681
• COBISS.SI-ID: 19536150

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: samorazvijajoči se sistemi, sprotno aktivno učenje iz toka podatkov, avtonomni razvoj skupine modelov

Projects

• Funder: Ministry of Culture and Science of the State of North Rhyne Westphalia
• Project number: NW21-059D
• Name: SAIL project

• Funder: National Council for Scientific and Technological Development Brazil
• Project number: 302467/2019–0