Analytical Methods in Fuzzy Modeling and Control:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2009
|
| Schriftenreihe: | Studies in Fuzziness and Soft Computing
241 |
| Schlagworte: | |
| Online-Zugang: | BTU01 FHN01 FHR01 Volltext |
| Beschreibung: | This book is focused on mathematical analysis and rigorous design methods for fuzzy control systems based on Takagi-Sugeno fuzzy models, sometimes called Takagi-Sugeno-Kang models. The author presents a rather general analytical theory of exact fuzzy modeling and control of continuous and discrete-time dynamical systems. Main attention is paid to usability of the results for the control and computer engineering community and therefore simple and easy knowledge-bases for linguistic interpretation have been used. The approach is based on the author’s theorems concerning equivalence between widely used Takagi-Sugeno systems and some class of multivariate polynomials. It combines the advantages of fuzzy system theory and classical control theory. Classical control theory can be applied to modeling of dynamical plants and the controllers. They are all equivalent to the set of Takagi-Sugeno type fuzzy rules. The approach combines the best of fuzzy and conventional control theory. It enables linguistic interpretability (also called transparency) of both the plant model and the controller. In the case of linear systems and some class of nonlinear systems, engineers can in many cases directly apply well-known classical tools from the control theory both for analysis, and the design of closed-loop fuzzy control systems. Therefore the main objective of the book is to establish comprehensive and unified analytical foundations for fuzzy modeling using the Takagi-Sugeno rule scheme and their applications for fuzzy control, identification of some class of nonlinear dynamical processes and classification problem solver design |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9783540899273 |
| DOI: | 10.1007/978-3-540-89927-3 |
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Datensatz im Suchindex
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| author | Kluska, Jasek |
| author_facet | Kluska, Jasek |
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| author_variant | j k jk |
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| contents | MISO Takagi-Sugeno Fuzzy System with Linear Membership Functions -- Recursion in TS Systems with Two Fuzzy Sets for Every Input -- Fuzzy Rule-Based Systems with Polynomial Membership Functions -- Comprehensive Study and Applications of P1-TS Systems -- Modeling of Multilinear Dynamical Systems from Experimental Data -- Binary Classification Using P1-TS Rule Scheme |
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| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik |
| doi_str_mv | 10.1007/978-3-540-89927-3 |
| format | Electronic eBook |
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| indexdate | 2024-07-10T01:07:32Z |
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| isbn | 9783540899273 |
| language | English |
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| spelling | Kluska, Jasek Verfasser aut Analytical Methods in Fuzzy Modeling and Control by Jasek Kluska Berlin, Heidelberg Springer Berlin Heidelberg 2009 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Studies in Fuzziness and Soft Computing 241 This book is focused on mathematical analysis and rigorous design methods for fuzzy control systems based on Takagi-Sugeno fuzzy models, sometimes called Takagi-Sugeno-Kang models. The author presents a rather general analytical theory of exact fuzzy modeling and control of continuous and discrete-time dynamical systems. Main attention is paid to usability of the results for the control and computer engineering community and therefore simple and easy knowledge-bases for linguistic interpretation have been used. The approach is based on the author’s theorems concerning equivalence between widely used Takagi-Sugeno systems and some class of multivariate polynomials. It combines the advantages of fuzzy system theory and classical control theory. Classical control theory can be applied to modeling of dynamical plants and the controllers. They are all equivalent to the set of Takagi-Sugeno type fuzzy rules. The approach combines the best of fuzzy and conventional control theory. It enables linguistic interpretability (also called transparency) of both the plant model and the controller. In the case of linear systems and some class of nonlinear systems, engineers can in many cases directly apply well-known classical tools from the control theory both for analysis, and the design of closed-loop fuzzy control systems. Therefore the main objective of the book is to establish comprehensive and unified analytical foundations for fuzzy modeling using the Takagi-Sugeno rule scheme and their applications for fuzzy control, identification of some class of nonlinear dynamical processes and classification problem solver design MISO Takagi-Sugeno Fuzzy System with Linear Membership Functions -- Recursion in TS Systems with Two Fuzzy Sets for Every Input -- Fuzzy Rule-Based Systems with Polynomial Membership Functions -- Comprehensive Study and Applications of P1-TS Systems -- Modeling of Multilinear Dynamical Systems from Experimental Data -- Binary Classification Using P1-TS Rule Scheme Engineering Artificial intelligence Engineering mathematics Control engineering systems Appl.Mathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Control , Robotics, Mechatronics Ingenieurwissenschaften Künstliche Intelligenz Fuzzy-Regelsystem (DE-588)4728095-5 gnd rswk-swf Mathematische Modellierung (DE-588)7651795-0 gnd rswk-swf Fuzzy-Regelsystem (DE-588)4728095-5 s Mathematische Modellierung (DE-588)7651795-0 s 1\p DE-604 Erscheint auch als Druckausgabe 978-3-540-89926-6 https://doi.org/10.1007/978-3-540-89927-3 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Kluska, Jasek Analytical Methods in Fuzzy Modeling and Control MISO Takagi-Sugeno Fuzzy System with Linear Membership Functions -- Recursion in TS Systems with Two Fuzzy Sets for Every Input -- Fuzzy Rule-Based Systems with Polynomial Membership Functions -- Comprehensive Study and Applications of P1-TS Systems -- Modeling of Multilinear Dynamical Systems from Experimental Data -- Binary Classification Using P1-TS Rule Scheme Engineering Artificial intelligence Engineering mathematics Control engineering systems Appl.Mathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Control , Robotics, Mechatronics Ingenieurwissenschaften Künstliche Intelligenz Fuzzy-Regelsystem (DE-588)4728095-5 gnd Mathematische Modellierung (DE-588)7651795-0 gnd |
| subject_GND | (DE-588)4728095-5 (DE-588)7651795-0 |
| title | Analytical Methods in Fuzzy Modeling and Control |
| title_auth | Analytical Methods in Fuzzy Modeling and Control |
| title_exact_search | Analytical Methods in Fuzzy Modeling and Control |
| title_full | Analytical Methods in Fuzzy Modeling and Control by Jasek Kluska |
| title_fullStr | Analytical Methods in Fuzzy Modeling and Control by Jasek Kluska |
| title_full_unstemmed | Analytical Methods in Fuzzy Modeling and Control by Jasek Kluska |
| title_short | Analytical Methods in Fuzzy Modeling and Control |
| title_sort | analytical methods in fuzzy modeling and control |
| topic | Engineering Artificial intelligence Engineering mathematics Control engineering systems Appl.Mathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Control , Robotics, Mechatronics Ingenieurwissenschaften Künstliche Intelligenz Fuzzy-Regelsystem (DE-588)4728095-5 gnd Mathematische Modellierung (DE-588)7651795-0 gnd |
| topic_facet | Engineering Artificial intelligence Engineering mathematics Control engineering systems Appl.Mathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Control , Robotics, Mechatronics Ingenieurwissenschaften Künstliche Intelligenz Fuzzy-Regelsystem Mathematische Modellierung |
| url | https://doi.org/10.1007/978-3-540-89927-3 |
| work_keys_str_mv | AT kluskajasek analyticalmethodsinfuzzymodelingandcontrol |