Fuzzy control systems: past, present and future

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dc.creatorAnh-Tu Nguyen
dc.creatorTadanari Taniguchi
dc.creatorLuka Eciolaza
dc.creatorVíctor Costa da Silva Campos
dc.creatorReinaldo Palhares
dc.creatorMichio Sugeno
dc.date.accessioned2025-05-13T14:54:29Z
dc.date.accessioned2025-09-09T00:03:43Z
dc.date.available2025-05-13T14:54:29Z
dc.date.issued2019
dc.identifier.doihttps://doi.org/10.1109/MCI.2018.2881644
dc.identifier.issn1556-603X
dc.identifier.urihttps://hdl.handle.net/1843/82227
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofIEEE Computational intelligence magazine
dc.rightsAcesso Restrito
dc.subjectSistemas difusos
dc.subject.otherControl System , Fuzzy System , Fuzzy Control , Types Of Systems , Control Approach , Systematic Framework , Asymptotically Stable , Matrix Inequalities , Fuzzy Logic , Model-based Approach , Expert Experience , Linear Matrix Inequalities , Fuzzy Approach , Control Design , Stability Analysis , Quadratic Function , Nonlinear Systems , Symmetric Matrix , Membership Function , Stability Conditions , Quadratic Lyapunov Function , Fuzzy Rules , Lyapunov Function , Fuzzy Set , Triangular Membership Functions , Premise Variables , Fuzzy Model , Stability Analysis Of Systems , Fault Detection And Isolation , Analysis Of Nonlinear Systems
dc.titleFuzzy control systems: past, present and future
dc.typeArtigo de periódico
local.citation.epage68
local.citation.spage56
local.citation.volume14
local.description.resumoMore than 40 years after fuzzy logic control appeared as an effective tool to deal with complex processes, the research on fuzzy control systems has constantly evolved. Mamdani fuzzy control was originally introduced as a model-free control approach based on expert?s experience and knowledge. Due to the lack of a systematic framework to study Mamdani fuzzy systems, we have witnessed growing interest in fuzzy model-based approaches with Takagi-Sugeno fuzzy systems and singleton-type fuzzy systems (also called piecewise multiaffine systems) over the past decades. This paper reviews the key features of the three above types of fuzzy systems. Through these features, we point out the historical rationale for each type of fuzzy systems and its current research mainstreams. However, the focus is put on fuzzy model-based approaches developed via Lyapunov stability theorem and linear matrix inequality (LMI) formulations. Finally, our personal viewpoint on the perspectives and challenges of the future fuzzy control research is discussed.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://ieeexplore.ieee.org/document/8610273

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