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Fuzzy Control Systems: Past, Present and Future

delete2019-02-01
delete235
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OA
AI
A
Anh‐Tu Nguyen *
T
Tadanari Taniguchi
L
Luka Eciolaza
V
Víctor Costa da Silva Campos
R
Reinaldo M. Palhares
M
Michio Sugeno
DOI:10.1109/MCI.2018.2881644delete
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摘要

摘要

En 中文
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 knowl-edge. 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.
Keyword:
OUTPUT-FEEDBACK CONTROL
LYAPUNOV FUNCTION-APPROACH
FAULT-TOLERANT CONTROL
H-INFINITY CONTROL
STABILITY ANALYSIS
NONLINEAR-SYSTEMS
RELAXED STABILITY
STABILIZATION CONDITIONS
CONTROL DESIGN
NONQUADRATIC STABILITY

期刊

IEEE Computational Intelligence Magazine 封面图
IEEE Computational Intelligence Magazine
IF:
11.2
论文数:
613
被引数:
3.1K

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U
universite polytechnique hauts-de-france
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1.3K
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Institute of Science Tokyo
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被引数: 117
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mondragon unibertsitatea
学者数:
1.2K
论文数: 767
被引数: 4
T
Tokai University
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5.8K
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被引数: 3.9K
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Universidade Federal de Minas Gerais
学者数:
2.5W
论文数: 1.5W
被引数: 1.4W
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