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category tags citekey status dateread
literaturenote
Fuzzy
control
Fuzzy
logic
Fuzzy
systems
Linguistics
Nonlinear
systems
Stability
analysis
Zadeh
Lotfi
LiteratureNote
nguyenFuzzyControlSystems2019 unread

[!Synth] Contribution::

Related::

[!md] FirstAuthor:: Nguyen, Anh-Tu
Author:: Taniguchi, Tadanari
Author:: Eciolaza, Luka
Author:: Campos, Victor
Author:: Palhares, Reinaldo
Author:: Sugeno, Michio
~
Title:: Fuzzy Control Systems: Past, Present and Future
Year:: 2019
Citekey:: nguyenFuzzyControlSystems2019
itemType:: journalArticle
Journal:: IEEE Computational Intelligence Magazine
Volume:: 14
Issue:: 1
Pages:: 56-68
DOI:: 10.1109/MCI.2018.2881644

[!LINK]

IEEE Xplore Full Text PDF.

[!Abstract]

More 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. .

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