LFLC 2000

LFLC 2000 (Linguistic Fuzzy Logic Controller) is specialized software, which is based on deep results obtained in formal theory of fuzzy logic. It makes it possible to deduce conclusions on the basis of imprecise description of the given situation using fuzzy IF-THEN rules. The rules are interpreted either as fuzzy relations, or they can be taken as genuine linguistic expressions and interpreted using the original theory developed in IRAFM. Sets of linguistically interpreted fuzzy IF-THEN rules are called linguistic descriptions. They can be understood as specific text describing the given process, decision, or classification situation. The users may thus work only with expressions of natural language without necessity to think how they are implemented. Hence, the computer behaves as if “partner” which understands the language of human user. LFLC 2000 is written in C++ under Windows and it is fully object oriented system. The system is integrated with other software LFLCSim using which we can simulate simple control in closed feedback loop. LFLC2000 is also joined with MATLAB/Simulink so that simulation of wide class of systems is possible. For theoretical background of LFLC, the following publications are recommended: detailed treatment of fuzzy logic can be found in [1]; the theory of trichotomous evaluative linguistic expressions is in detail explained in [2]; the theory of perception–based logical deduction can be found in [3], [4], [5]. For explanation of representation of fuzzy logic functions by normal forms see [6].


References in zbMATH (referenced in 12 articles )

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  1. Volna, Eva; Jarusek, Robert; Kotyrba, Martin; Zacek, Jaroslav: Training set fuzzification based on histogram to increase the performance of a neural network (2021)
  2. Dvořák, Antonín; Štěpnička, Martin; Štěpničková, Lenka: On redundancies in systems of fuzzy/linguistic IF-THEN rules under perception-based logical deduction inference (2015)
  3. Klimeš, Cyril; Bartoš, Jiří: IT/IS security management with uncertain information. (2015)
  4. Dvořák, Antonín; Štěpnička, Martin; Vavříčková, Lenka: Redundancies in systems of fuzzy/linguistic IF-THEN rules (2011)
  5. Štěpnička, Martin; Dvořák, Antonín; Pavliska, Viktor; Vavříčková, Lenka: A linguistic approach to time series modeling with the help of F-transform (2011)
  6. Novák, Vilém; Štěpnička, Martin; Dvořák, Antonín; Perfilieva, Irina; Pavliska, Viktor; Vavříčková, Lenka: Analysis of seasonal time series using fuzzy approach (2010)
  7. Novák, Vilém: A comprehensive theory of trichotomous evaluative linguistic expressions (2008)
  8. Di Nola, Antonio; Lettieri, Ada; Perfilieva, Irina; Novák, Vilém: Algebraic analysis of fuzzy systems (2007)
  9. Dvořák, A.; Novák, V.: Towards automatic modeling of economic texts (2007)
  10. Novák, Vilém: Mathematical fuzzy logic in modeling of natural language semantics (2007)
  11. Novák, Vilém; Lehmke, Stephan: Logical structure of fuzzy IF-THEN rules (2006)
  12. Novák, Vilém; Perfilieva, Irina: On the semantics of perception-based fuzzy logic deduction (2004)