Fuzzy Logic Control Systems
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".
Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 3277
Special Issue Editors
Interests: artificial intelligence; natural language processing; knowledge representation
Special Issues, Collections and Topics in MDPI journals
Interests: economic cybernetics; consumer behavior; agent-based modeling; sustainable development; gray systems theory; neutrosophic theory
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue of the open-access journal Mathematics (ISSN 2227-7390) will publish new results in the field of fuzzy logic control systems using theories, concepts, and algorithms that extend the original ideas of the pioneering work of Prof. L. A. Zadeh. Traditional fuzzy logic or type-1 fuzzy logic has been widely used in various decision-making models using different fuzzy-logic based approaches.
Mainly because fuzzy logic has emerged as a powerful representation method in handling vague estimates, several logics were developed to capture fuzziness, imprecision, and uncertainty of data.
In the seventies, Zadeh, Grattan-Guinness, Jahn, and Sambuc independently introduced interval-valued fuzzy sets (IVFS) in which the set membership is treated as an interval.
Later, Belnap defined four-valued logic to cope with multiple information sources.
Rough set theory was developed by Pawlak in the eighties, which was found useful for decision-making applications in different domains.
K. Atanassov extended fuzzy logic to Intuitionistic fuzzy sets (IFS) and then, to allow greater freedom and flexibility in representing uncertainty, interval-valued intuitionistic fuzzy sets (IVIFS) were proposed.
Vague sets defined as sets of objects having a grade of membership value as a continuous subinterval of [0, 1] were introduced in the literature by Gau and Buehrer in the nineties.
In 1998 F. Smarandache proposed the Neutrosophic Logic and, quite recently (in 2013), refined neutrosophic logic (which generalizes Belnap's four-valued logic) to represent mathematical models of uncertainty, vagueness, ambiguity, imprecision, incompleteness, inconsistency, redundancy, and contradiction.
For this Special Issue, authors are invited to publish new theories, concepts, and algorithms related to all these fuzzy logic extensions in conjunction with control systems development and with linguistic knowledge deduced from expert knowledge on control issues.
Prof. Dr. Mihaela Colhon
Prof. Camelia Delcea
Prof. Dr. Maikel Yelandi Leyva Vázquez
Guest Editors
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Keywords
- Fuzzy mathematics for fuzzy controllers
- Fuzzy modeling
- Takagi–Sugeno structures
- Optimization-based fuzzy control
- Fuzzy algorithms for search, classification, approximation, and learning
- Type 2 fuzzy controllers
- Intuitionistic fuzzy logic control
- Neutrosophic logic control
- Fuzzy refined neutrosophic logic control
- Picture fuzzy logic control
- Intelligent control
- Fuzzy expert systems
- Technologies and applications
- Implementation of fuzzy control structures in fuzzy control languages
- Industrial application of fuzzy control
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