Design of Adaptive T-S Fuzzy-Neural Controller for a Class of Robot Manipulators Using Projection Update Laws

dc.contributor國立臺灣師範大學電機工程學系zh_tw
dc.contributor.authorY.-H. Chienen_US
dc.contributor.authorW.-Y. Wangen_US
dc.contributor.authorT.-T. Leeen_US
dc.date.accessioned2014-10-30T09:28:18Z
dc.date.available2014-10-30T09:28:18Z
dc.date.issued2010-10-13zh_TW
dc.description.abstractAn on-line tracking controller design based on using T-S fuzzy-neural modeling for a class of general robot manipulators is investigated in this paper. Also, we use rojection update laws to tune adjustable parameters for preventing parameters drift. In addition, stability of the closed-loop systems is proven by using strictly-positive-real (SPR) Lyapunov theory. The proposed overall scheme guarantees that all signals involved are bounded and the outputs of the closed-loop system asymptotically track the desired output trajectories. Finally, an example including two cases confirms the effectiveness of the proposed method.en_US
dc.description.urihttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5642419zh_TW
dc.identifierntnulib_tp_E0604_02_014zh_TW
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/31991
dc.languageenzh_TW
dc.relationEEE International Conference on Systems, Man and Cybernetics,Istanbul,Turkey, pp. 1255-1260en_US
dc.subject.otherT-S fuzzy-neural modelen_US
dc.subject.otherprojection update lawen_US
dc.subject.otherrobot manipulatoren_US
dc.titleDesign of Adaptive T-S Fuzzy-Neural Controller for a Class of Robot Manipulators Using Projection Update Lawsen_US

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