DC Field | Value | Language |
---|---|---|
dc.contributor.author | Nam, K | - |
dc.date.accessioned | 2016-03-31T13:42:06Z | - |
dc.date.available | 2016-03-31T13:42:06Z | - |
dc.date.created | 2009-03-19 | - |
dc.date.issued | 1999-05 | - |
dc.identifier.issn | 0018-9286 | - |
dc.identifier.other | 1999-OAK-0000000738 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/20413 | - |
dc.description.abstract | The main obstacle in the practical use of the feedback linearization is the difficulty in obtaining a linearizing feedback and a coordinate transformation map. Finding a desired transformation map and feedback turns out to be finding an integrating factor for an annihilating one-form. In this work, we develop numerical algorithms for an integrating factor and the corresponding zero-form. Employing a radial basis function (RBF) neural network as an interpolation method for the data resulted from the numerical algorithms, the authors obtained an approximate integrating factor and zero-form in closed forms. Finally, they construct a stabilizing controller based on a linearized system with the use of the approximate integrating factor and zero-form. | - |
dc.description.statementofresponsibility | X | - |
dc.language | English | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGI | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON AUTOMATIC CONTROL | - |
dc.subject | approximate integrating factor | - |
dc.subject | feedback linearization | - |
dc.subject | RBF neural network | - |
dc.subject | NEURAL NETWORKS | - |
dc.subject | DYNAMIC-SYSTEMS | - |
dc.title | Stabilization of feedback linearizable systems using a radial basis function network | - |
dc.type | Article | - |
dc.contributor.college | 전자전기공학과 | - |
dc.identifier.doi | 10.1109/9.763222 | - |
dc.author.google | Nam, K | - |
dc.relation.volume | 44 | - |
dc.relation.issue | 5 | - |
dc.relation.startpage | 1026 | - |
dc.relation.lastpage | 1031 | - |
dc.contributor.id | 10071835 | - |
dc.relation.journal | IEEE TRANSACTIONS ON AUTOMATIC CONTROL | - |
dc.relation.index | SCI급, SCOPUS 등재논문 | - |
dc.relation.sci | SCI | - |
dc.collections.name | Journal Papers | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON AUTOMATIC CONTROL, v.44, no.5, pp.1026 - 1031 | - |
dc.identifier.wosid | 000080335000017 | - |
dc.date.tcdate | 2019-01-01 | - |
dc.citation.endPage | 1031 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 1026 | - |
dc.citation.title | IEEE TRANSACTIONS ON AUTOMATIC CONTROL | - |
dc.citation.volume | 44 | - |
dc.contributor.affiliatedAuthor | Nam, K | - |
dc.identifier.scopusid | 2-s2.0-0032630079 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 24 | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | approximate integrating factor | - |
dc.subject.keywordAuthor | feedback linearization | - |
dc.subject.keywordAuthor | RBF neural network | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Engineering | - |
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