DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, CY | ko |
dc.contributor.author | Lee, Ju-Jang | ko |
dc.date.accessioned | 2009-01-09T07:40:01Z | - |
dc.date.available | 2009-01-09T07:40:01Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2005-02 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, v.52, pp.320 - 326 | - |
dc.identifier.issn | 0278-0046 | - |
dc.identifier.uri | http://hdl.handle.net/10203/8267 | - |
dc.description.abstract | A new adaptive controller based on multiple neural networks (NNs) for an uncertain robot manipulator system is developed in this paper. The proposed multiple neuro-adaptive controller (MNAC) switches to a memorized control skill or blends multiple skills by using visual information on the given job to improve the transient response at the time of task variation like a change of manipulating object. MNAC is a type of adaptive feedback controller where system nonlinearity terms are approximated with multiple NNs. The proposed controller is effective for a job where some tasks are repeated but information on the load cannot be scheduled before the operation. During the learning phase, MNAC memorizes a control skill for each load with each NN. For a new task, most similar existing control skills may be used as a starting point of adaptation, which improves the performance of learning. Lyapunov-function-based design of MNAC guarantees the stability of the closed-loop system to be independent of switching or blending law. Simulation results on a two-link manipulator for changing the mass of the given load were illustrated to show the effectiveness of the proposed control scheme by comparison with the conventional neuro-adaptive controller. | - |
dc.language | English | - |
dc.language.iso | en_US | en |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | NONLINEAR DYNAMICAL-SYSTEMS | - |
dc.subject | GAUSSIAN NETWORKS | - |
dc.subject | OBSERVER | - |
dc.subject | MODELS | - |
dc.subject | DESIGN | - |
dc.subject | OUTPUT | - |
dc.title | Multiple neuro-adaptive control of robot manipulators using visual cues | - |
dc.type | Article | - |
dc.identifier.wosid | 000226755900036 | - |
dc.identifier.scopusid | 2-s2.0-13944250618 | - |
dc.type.rims | ART | - |
dc.citation.volume | 52 | - |
dc.citation.beginningpage | 320 | - |
dc.citation.endingpage | 326 | - |
dc.citation.publicationname | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | - |
dc.identifier.doi | 10.1109/TIE.2004.841080 | - |
dc.contributor.localauthor | Lee, Ju-Jang | - |
dc.contributor.nonIdAuthor | Lee, CY | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | adaptive control | - |
dc.subject.keywordAuthor | intelligent control | - |
dc.subject.keywordAuthor | neural networks (NNs) | - |
dc.subject.keywordAuthor | robot manipulators | - |
dc.subject.keywordAuthor | switching control | - |
dc.subject.keywordPlus | NONLINEAR DYNAMICAL-SYSTEMS | - |
dc.subject.keywordPlus | GAUSSIAN NETWORKS | - |
dc.subject.keywordPlus | OBSERVER | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordPlus | DESIGN | - |
dc.subject.keywordPlus | OUTPUT | - |
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