Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.neucom.2007.02.012
DC FieldValue
dc.titleAdaptive neural network algorithm for control design of rigid-link electrically driven robots
dc.contributor.authorHuang, S.N.
dc.contributor.authorTan, K.K.
dc.contributor.authorLee, T.H.
dc.date.accessioned2014-06-17T02:36:57Z
dc.date.available2014-06-17T02:36:57Z
dc.date.issued2008-01
dc.identifier.citationHuang, S.N., Tan, K.K., Lee, T.H. (2008-01). Adaptive neural network algorithm for control design of rigid-link electrically driven robots. Neurocomputing 71 (4-6) : 885-894. ScholarBank@NUS Repository. https://doi.org/10.1016/j.neucom.2007.02.012
dc.identifier.issn09252312
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/54914
dc.description.abstractIn this article, an adaptive neural network algorithm is developed for control issue of rigid-link electrically-driven (RLED) robot systems. First, an virtual control algorithm is designed to deal with the mechanical dynamics. Next, an actual neural network controller is used to handle the uncertainty in the mechanical and electrical dynamics. The stability is guaranteed by using a rigid stability proof. Finally, a simulation is given to show the effectiveness of the proposed algorithm. © 2007 Elsevier B.V. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.neucom.2007.02.012
dc.sourceScopus
dc.subjectAdaptive control
dc.subjectNeural network
dc.subjectRadial basis function
dc.subjectRobotic systems
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1016/j.neucom.2007.02.012
dc.description.sourcetitleNeurocomputing
dc.description.volume71
dc.description.issue4-6
dc.description.page885-894
dc.description.codenNRCGE
dc.identifier.isiut000253663800047
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