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Conference Paper: Model reference adaptive fuzzy control of robot manipulator

TitleModel reference adaptive fuzzy control of robot manipulator
Authors
Issue Date1995
Citation
Proceedings Of The Ieee International Conference On Systems, Man And Cybernetics, 1995, v. 1, p. 424-429 How to Cite?
AbstractAn Model Reference Adaptive Fuzzy Control, MRAFC, scheme for manipulator control is proposed to incorporate with nonlinear and time-varying dynamic behavior of the system. The scheme employs a reference model to provide closed-loop performance feedback. The basic idea of MRAFC scheme for manipulator control is to perform adaptive feedback linearization, i.e. to asymptotically cancel the nonlinearity in the system and place system poles in the desired locations as specified in the reference model. The type of controller used is a class of fuzzy controllers [2], which can be expressed in an explicit form. The stability of the fuzzy rule adaptive laws is assured by the existence of the Lyapunov function. In the simulation, two adaptive fuzzy controllers are applied on a two-link manipulator. The results show that MRAFC system is stable and the performance in tracking the reference model response can be improved by simply repeating the same task.
Persistent Identifierhttp://hdl.handle.net/10722/188687
ISSN

 

DC FieldValueLanguage
dc.contributor.authorKoo, TakKuen Johnen_US
dc.date.accessioned2013-09-03T04:13:08Z-
dc.date.available2013-09-03T04:13:08Z-
dc.date.issued1995en_US
dc.identifier.citationProceedings Of The Ieee International Conference On Systems, Man And Cybernetics, 1995, v. 1, p. 424-429en_US
dc.identifier.issn0884-3627en_US
dc.identifier.urihttp://hdl.handle.net/10722/188687-
dc.description.abstractAn Model Reference Adaptive Fuzzy Control, MRAFC, scheme for manipulator control is proposed to incorporate with nonlinear and time-varying dynamic behavior of the system. The scheme employs a reference model to provide closed-loop performance feedback. The basic idea of MRAFC scheme for manipulator control is to perform adaptive feedback linearization, i.e. to asymptotically cancel the nonlinearity in the system and place system poles in the desired locations as specified in the reference model. The type of controller used is a class of fuzzy controllers [2], which can be expressed in an explicit form. The stability of the fuzzy rule adaptive laws is assured by the existence of the Lyapunov function. In the simulation, two adaptive fuzzy controllers are applied on a two-link manipulator. The results show that MRAFC system is stable and the performance in tracking the reference model response can be improved by simply repeating the same task.en_US
dc.languageengen_US
dc.relation.ispartofProceedings of the IEEE International Conference on Systems, Man and Cyberneticsen_US
dc.titleModel reference adaptive fuzzy control of robot manipulatoren_US
dc.typeConference_Paperen_US
dc.identifier.emailKoo, TakKuen John: john.koo@siat.ac.cnen_US
dc.identifier.authorityKoo, TakKuen John=rp01787en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0029485274en_US
dc.identifier.volume1en_US
dc.identifier.spage424en_US
dc.identifier.epage429en_US
dc.identifier.scopusauthoridKoo, TakKuen John=7005428593en_US

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