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Singleton-Based Two-String Inference in Recurrent Fuzzy Systems

Schneider, Moritz ; Adamy, Jürgen (2023)
Singleton-Based Two-String Inference in Recurrent Fuzzy Systems.
In: IFAC Proceedings Volumes, 2014, 47 (3)
doi: 10.26083/tuprints-00023293
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Singleton-Based Two-String Inference in Recurrent Fuzzy Systems
Language: English
Date: 2023
Place of Publication: Darmstadt
Year of primary publication: 2014
Publisher: IFAC - International Federation of Automatic Control
Journal or Publication Title: IFAC Proceedings Volumes
Volume of the journal: 47
Issue Number: 3
DOI: 10.26083/tuprints-00023293
Corresponding Links:
Origin: Secondary publication service

Two-string fuzzy inference consists of two separate inference mechanisms: One conventional fuzzy inference system that processes recommending rules, as well as a mechanism for processing negative rules, which prevent the system from outputting their associated values when their premise is fulfilled. Two-string inference has valuable applications in pattern recognition and control tasks. We present a method rendering two-string inference applicable and computationally feasible in recurrent fuzzy systems, i.e. Mamdami-type fuzzy inference systems equipped with defuzzified state feedback. We show the efficiency of our approach by means of an illustrative example from biological systems modelling and suggest application areas for recurrent two-string fuzzy systems.

Uncontrolled Keywords: Recurrent Fuzzy Systems, Fuzzy Inference, Rule-based Systems, Dynamic modelling, Fuzzy modelling, Fuzzy control
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-232931
Additional Information:

Zugl. Konferenzveröffentlichung: 19th IFAC World Congress (IFAC 2014), 24.-29.08.2014, Cape Town, South Africa

Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Intelligent Systems
Date Deposited: 01 Mar 2023 13:41
Last Modified: 26 May 2023 07:05
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23293
PPN: 507989252
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