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Fuzzy associative matrix

About: Fuzzy associative matrix is a research topic. Over the lifetime, 8027 publications have been published within this topic receiving 194790 citations.


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Journal ArticleDOI
TL;DR: The procedures here will allow to set up linear matrix inequality conditions which are less conservative than the cited ones, by exploiting the TP structure of the membership functions.

83 citations

Journal ArticleDOI
TL;DR: A notion of fuzzy function and its representation by fuzzy relation is introduced and it is shown that fuzzy relations introduced by Sanchez and Mamdani are the best approximations in certain approximation spaces.

83 citations

Proceedings ArticleDOI
26 Jun 1994
TL;DR: A design problem for a fuzzy regulator which consists of fuzzy state feedback laws is solved by extending the idea of modem control theory and the concept of a fuzzy observer, which estimates the states of fuzzy dynamic plants, is introduced.
Abstract: Deals with design procedures for fuzzy regulators and fuzzy observers, which are the most important and basic concepts for fuzzy control system design. First, a design problem for a fuzzy regulator which consists of fuzzy state feedback laws is solved by extending the idea of modem control theory. Next, the concept of a fuzzy observer, which estimates the states of fuzzy dynamic plants, is introduced. Finally, a design algorithm for a fuzzy control system containing a fuzzy regulator and a fuzzy observer is constructed. The fuzzy regulator guarantees the stability of the fuzzy control system in accordance with the definition of stability in the sense of Lyapunov. The fuzzy observer guarantees that the estimation error for the states of the fuzzy dynamic plants converges to zero. The 'separate theorem', which guarantees that one should be able to design regulators and observers separately, cannot be applied to the case of the design of fuzzy regulators and fuzzy observers. >

83 citations

Proceedings ArticleDOI
01 Jan 1993
TL;DR: The authors show how to model the Mackey-Glass chaotic time series with 16 fuzzy if-then rules, which outperforms various standard statistical approaches and artificial neural network modeling methods reported in the literature.
Abstract: The authors continue work on a previously proposed ANFIS (adaptive-network-based fuzzy inference system) architecture, with emphasis on the applications to time series prediction. They show how to model the Mackey-Glass chaotic time series with 16 fuzzy if-then rules. The performance obtained outperforms various standard statistical approaches and artificial neural network modeling methods reported in the literature. Other potential applications of ANFIS are also suggested. >

83 citations

Journal ArticleDOI
TL;DR: The concept from the sliding mode control is adopted to construct fuzzy control scheme and the structure of sliding surface provides a reasonable estimation to the universes of discourse on which the fuzzy control rules are based.

83 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20238
202216
20212
20201
20193
201825