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Type-2 fuzzy logic: uncertain systems’ modeling and control

This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the princip...

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Detalles Bibliográficos
Autor principal: Antão, Rómulo
Lenguaje:eng
Publicado: Springer 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-981-10-4633-9
http://cds.cern.ch/record/2276991
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author Antão, Rómulo
author_facet Antão, Rómulo
author_sort Antão, Rómulo
collection CERN
description This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets. Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.
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spelling cern-22769912021-04-21T19:08:17Zdoi:10.1007/978-981-10-4633-9http://cds.cern.ch/record/2276991engAntão, RómuloType-2 fuzzy logic: uncertain systems’ modeling and controlMathematical Physics and MathematicsThis book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets. Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.Springeroai:cds.cern.ch:22769912017
spellingShingle Mathematical Physics and Mathematics
Antão, Rómulo
Type-2 fuzzy logic: uncertain systems’ modeling and control
title Type-2 fuzzy logic: uncertain systems’ modeling and control
title_full Type-2 fuzzy logic: uncertain systems’ modeling and control
title_fullStr Type-2 fuzzy logic: uncertain systems’ modeling and control
title_full_unstemmed Type-2 fuzzy logic: uncertain systems’ modeling and control
title_short Type-2 fuzzy logic: uncertain systems’ modeling and control
title_sort type-2 fuzzy logic: uncertain systems’ modeling and control
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-981-10-4633-9
http://cds.cern.ch/record/2276991
work_keys_str_mv AT antaoromulo type2fuzzylogicuncertainsystemsmodelingandcontrol