File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: 神経回路モデルによるロボットマニピュレータの位置・力制御の研究 (第6報, ニューロモーフィック制御とシンボリック制御による階層的知的制御システム)

Title神経回路モデルによるロボットマニピュレータの位置・力制御の研究 (第6報, ニューロモーフィック制御とシンボリック制御による階層的知的制御システム)
Hybrid Control of a Robotic Manipulator by the Neural Network Model (6th Report, Hierarchical Intelligent Control System)
Authors
Shibata, TakanoriFukuda, ToshioKosuge, KazuhiroArai, FumihitoTokita, MasatoshiMitsuoka, Toyokazu
KeywordsNeural Network
Planning
Control
Robotics
Hybrid System
Artificial Intelligence
Knowledge Base
Recognition
Issue Date1992
Citation
日本機械学会論文集Ｃ編, 1992, v. 58, n. 549, p. 1442-1449 How to Cite?
DOI: http://dx.doi.org/10.1299/kikaic.58.1442
Transactions of the Japan Society of Mechanical Engineers Series C, 1992, v. 58, n. 549, p. 1442-1449 How to Cite?
DOI: http://dx.doi.org/10.1299/kikaic.58.1442
AbstractIn this paper, we present a new scheme for intelligent control of robotic manipulators. This scheme is an integrated approach of the Neuromorphic and Symbolic control, including the applied neural network for the servo control and the knowledge-based approximation. The neural network in the servo level is the numerical manipulation, while the knowledge-based part is the symbolic manipulation. In Neuromorphic control, the neural network compensates the nonlinearity of the system and the uncertainty in environment. The knowledge-base part forms symbolic control strategy for the servo level. This is control system analogous to the human cerebral control structure. © 1992, The Japan Society of Mechanical Engineers. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/302960
ISSN
0387-5024
2019 SCImago Journal Rankings: 0.104

 

DC FieldValueLanguage
dc.contributor.authorShibata, Takanori-
dc.contributor.authorFukuda, Toshio-
dc.contributor.authorKosuge, Kazuhiro-
dc.contributor.authorArai, Fumihito-
dc.contributor.authorTokita, Masatoshi-
dc.contributor.authorMitsuoka, Toyokazu-
dc.date.accessioned2021-09-07T08:42:55Z-
dc.date.available2021-09-07T08:42:55Z-
dc.date.issued1992-
dc.identifier.citation日本機械学会論文集Ｃ編, 1992, v. 58, n. 549, p. 1442-1449-
dc.identifier.citationTransactions of the Japan Society of Mechanical Engineers Series C, 1992, v. 58, n. 549, p. 1442-1449-
dc.identifier.issn0387-5024-
dc.identifier.urihttp://hdl.handle.net/10722/302960-
dc.description.abstractIn this paper, we present a new scheme for intelligent control of robotic manipulators. This scheme is an integrated approach of the Neuromorphic and Symbolic control, including the applied neural network for the servo control and the knowledge-based approximation. The neural network in the servo level is the numerical manipulation, while the knowledge-based part is the symbolic manipulation. In Neuromorphic control, the neural network compensates the nonlinearity of the system and the uncertainty in environment. The knowledge-base part forms symbolic control strategy for the servo level. This is control system analogous to the human cerebral control structure. © 1992, The Japan Society of Mechanical Engineers. All rights reserved.-
dc.languagejpn-
dc.relation.ispartof日本機械学会論文集Ｃ編-
dc.relation.ispartofTransactions of the Japan Society of Mechanical Engineers Series C-
dc.subjectNeural Network-
dc.subjectPlanning-
dc.subjectControl-
dc.subjectRobotics-
dc.subjectHybrid System-
dc.subjectArtificial Intelligence-
dc.subjectKnowledge Base-
dc.subjectRecognition-
dc.title神経回路モデルによるロボットマニピュレータの位置・力制御の研究 (第6報, ニューロモーフィック制御とシンボリック制御による階層的知的制御システム)-
dc.titleHybrid Control of a Robotic Manipulator by the Neural Network Model (6th Report, Hierarchical Intelligent Control System)-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1299/kikaic.58.1442-
dc.identifier.scopuseid_2-s2.0-84996039900-
dc.identifier.volume58-
dc.identifier.issue549-
dc.identifier.spage1442-
dc.identifier.epage1449-

Export via OAI-PMH Interface in XML Formats

OR

Export to Other Non-XML Formats