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Learning strategy for optimal fuzzy control

dc.contributor.authorSalgado, Paulo
dc.contributor.authorIgrejas, GetĂșlio
dc.date.accessioned2010-11-10T10:10:28Z
dc.date.available2010-11-10T10:10:28Z
dc.date.issued2007
dc.description.abstractIn this paper, a new scheme of fuzzy optimal control for discrete-time nonlinear systems based on the Pontryagin’s Minimum Principle is proposed. Using back propagation from the final co-state error and gradient descent, a method which allows training an adaptive fuzzy inference system to estimate values for the co-state variables converging to the optimal ones is devised. This approach allows finding a solution to the optimal control problem on-line by training the system, rather than by pre-computing it. Finally, this optimal approach is applied to nonlinear control benchmark problems. The results demonstrate the effectiveness of the approach towards achieving the optimal control objective.por
dc.description.sponsorshipThis work was supported by the Portuguese "Fundação para a CiĂȘncia e a Tecnologia (FCT)" under grant POSI/SRI/41975/2001.
dc.identifier.citationSalgado, Paulo; Igrejas, GetĂșlio (2007). Learning strategy for optimal fuzzy control. In IEEE International Symposium on on Industrial Electronics. Vigopor
dc.identifier.urihttp://hdl.handle.net/10198/2784
dc.language.isoengpor
dc.subjectFuzzy systemspor
dc.subjectOptimalpor
dc.titleLearning strategy for optimal fuzzy controlpor
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/Orçamento de Funcionamento%2FPOSC/POSI%2FSRI%2F41975%2F2001/PT
oaire.citation.conferencePlaceVigo - Espanhapor
oaire.citation.titleIEEE International Symposium on on Industrial Electronicspor
oaire.fundingStreamOrçamento de Funcionamento/POSC
person.familyNameIgrejas
person.givenNameGetĂșlio
person.identifier.orcid0000-0002-6820-8858
person.identifier.ridM-8571-2013
person.identifier.scopus-author-id47761255900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a CiĂȘncia e a Tecnologia
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor
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relation.isAuthorOfPublication.latestForDiscoveryab4092ec-d1b1-4fe0-b65a-efba1310fd5a
relation.isProjectOfPublication154760fe-aeaf-4771-88e0-55ec65fc7d00
relation.isProjectOfPublication.latestForDiscovery154760fe-aeaf-4771-88e0-55ec65fc7d00

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