Recursive neuro fuzzy techniques for online identification and control

Detalhes bibliográficos
Autor(a) principal: Oliveira, Tiago Miguel Brites
Data de Publicação: 2013
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/10552
Resumo: Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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spelling Recursive neuro fuzzy techniques for online identification and controlRecursive optimizationOnline identificationAdaptative controlSelf learningKalman filteringUnscented transformationDissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresThe main goal of this thesis will be focused on developing an adaptative closed loop control solution, using fuzzy methodologies. A positive theoretical and experimental contribution, regarding modelling and control of fuzzy and neuro fuzzy systems, is expected to be achieved. Proposed non-linear identification solution will use for modelling and control, a recurrent neuro fuzzy architecture. Regarding model solution, a state space approach will be considered during fuzzy consequent local models design. Developed controller will be based on model parameters, being expected not only a stable closed loop solution, but also a static error with convergence towards zero. Model and controller fuzzy subspaces, will be partitioned throughout process dynamical universe, allowing fuzzy local models and controllers commutation and aggregation. With the aim of capturing process under control dynamics using a real time approach, the use of recursive optimization techniques are to be adopted. Such methods will be applied during parameter and state estimation, using a dual decoupled Kalman filter extended with unscented transformation. Two distinct processes one single-input (SISO) other multi-input (MIMO), will be used during experimentation. It is expected from experiments, a practical validation of proposed solution capabilities for control and identification. Presented work will not be completed, without first presenting a global analysis of adopted concepts and methods, describing new perspectives for future investigations.Faculdade de Ciências e TecnologiaPalma, LuísGil, PauloRUNOliveira, Tiago Miguel Brites2013-10-14T13:30:47Z20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/10552enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-10T15:29:44ZPortal AgregadorONG
dc.title.none.fl_str_mv Recursive neuro fuzzy techniques for online identification and control
title Recursive neuro fuzzy techniques for online identification and control
spellingShingle Recursive neuro fuzzy techniques for online identification and control
Oliveira, Tiago Miguel Brites
Recursive optimization
Online identification
Adaptative control
Self learning
Kalman filtering
Unscented transformation
title_short Recursive neuro fuzzy techniques for online identification and control
title_full Recursive neuro fuzzy techniques for online identification and control
title_fullStr Recursive neuro fuzzy techniques for online identification and control
title_full_unstemmed Recursive neuro fuzzy techniques for online identification and control
title_sort Recursive neuro fuzzy techniques for online identification and control
author Oliveira, Tiago Miguel Brites
author_facet Oliveira, Tiago Miguel Brites
author_role author
dc.contributor.none.fl_str_mv Palma, Luís
Gil, Paulo
RUN
dc.contributor.author.fl_str_mv Oliveira, Tiago Miguel Brites
dc.subject.por.fl_str_mv Recursive optimization
Online identification
Adaptative control
Self learning
Kalman filtering
Unscented transformation
topic Recursive optimization
Online identification
Adaptative control
Self learning
Kalman filtering
Unscented transformation
description Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
publishDate 2013
dc.date.none.fl_str_mv 2013-10-14T13:30:47Z
2013
2013-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/10552
url http://hdl.handle.net/10362/10552
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Faculdade de Ciências e Tecnologia
publisher.none.fl_str_mv Faculdade de Ciências e Tecnologia
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv
repository.mail.fl_str_mv
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