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Application of N-step-ahead neurocontrol on articulated manipulators

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dc.contributor.author Hountras, A en
dc.contributor.author Antoniadis, I en
dc.contributor.author Kanarachos, A en
dc.date.accessioned 2014-03-01T01:15:29Z
dc.date.available 2014-03-01T01:15:29Z
dc.date.issued 2000 en
dc.identifier.issn 0741-2223 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/13532
dc.subject.classification Robotics en
dc.subject.other NEURAL NETWORKS en
dc.subject.other SYSTEM-IDENTIFICATION en
dc.subject.other DYNAMIC-SYSTEMS en
dc.subject.other CONTROLLERS en
dc.subject.other MODELS en
dc.title Application of N-step-ahead neurocontrol on articulated manipulators en
heal.type journalArticle en
heal.identifier.primary 10.1002/(SICI)1097-4563(200003)17:3<127::AID-ROB1>3.3.CO;2-P en
heal.identifier.secondary http://dx.doi.org/10.1002/(SICI)1097-4563(200003)17:3<127::AID-ROB1>3.3.CO;2-P en
heal.language English en
heal.publicationDate 2000 en
heal.abstract The N-step-ahead control method, called chain-back-propagation, is applied to articulated manipulators. The method is based on a pair of: neural networks-the neural controller and the neural emulator-and focuses mainly in the appropriate design of the various global and chain-local penalty functions and the convergence control limitations, needed for the on-line training of the controller. No reference models or paths are needed for the implementation of the method, only set-points. The results, compared to conventional proportional-derivative (PD) control and to traditional one-step-ahead neural control, are quite satisfactory, indicating improved accuracy, faster response, and greater overall efficiency, (C) 2000 John Wiley & Sons, Inc. en
heal.publisher JOHN WILEY & SONS INC en
heal.journalName JOURNAL OF ROBOTIC SYSTEMS en
dc.identifier.doi 10.1002/(SICI)1097-4563(200003)17:3<127::AID-ROB1>3.3.CO;2-P en
dc.identifier.isi ISI:000085562100001 en
dc.identifier.volume 17 en
dc.identifier.issue 3 en
dc.identifier.spage 127 en
dc.identifier.epage 148 en


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