T-S Fuzzy-Neural Control for Robot Manipulators

dc.contributor國立臺灣師範大學電機工程學系zh_tw
dc.contributor.authorW.-Y. Wangen_US
dc.contributor.authorY.-H. Chienen_US
dc.contributor.authorY.-G. Leuen_US
dc.contributor.authorZ.-H. Leeen_US
dc.contributor.authorT.-T. Leeen_US
dc.date.accessioned2014-10-30T09:28:20Z
dc.date.available2014-10-30T09:28:20Z
dc.date.issued2008-08-25zh_TW
dc.description.abstractThis paper proposes a novel method of on-line modeling and control through the Takagi-Sugeno (T-S) fuzzy-neural model for a class of general n-link robot manipulators. Compared with the previous method, the main contribution of this paper is an investigation of the more general robot systems using on-line adaptive T-S fuzzy-neural controller. Specifically, the general robot systems are exactly formed a linearized system via the mean value theorem, and then the T-S fuzzy-neural model can approximate the linearized system. Also, we propose an on-line identification algorithm and put significant emphasis on robust tracking controller design using an adaptive scheme for the robot systems. Finally, an example including two cases is provided to demonstrate feasibility and robustness of the proposed method.en_US
dc.description.urihttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4653613zh_TW
dc.identifierntnulib_tp_E0604_02_032zh_TW
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/32009
dc.languageenzh_TW
dc.relation2008 EE International Conference on Advanced Robotics and its Social Impacts,aipei,pp1-6en_US
dc.titleT-S Fuzzy-Neural Control for Robot Manipulatorsen_US

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