H-inf.-observer-based adaptive fuzzy-neural control for a class of uncertain nonlinear systems

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dc.contributor國立臺灣師範大學電機工程學系zh_tw
dc.contributor.authorY.-G. Leuen_US
dc.contributor.authorW.-Y. Wangen_US
dc.contributor.authorT.-T. Leeen_US
dc.date.accessioned2014-10-30T09:28:25Z
dc.date.available2014-10-30T09:28:25Z
dc.date.issued1999-10-15zh_TW
dc.description.abstractThis paper presents a method for designing an H∞-observer-based adaptive fuzzy-neural output feedback control law with on-line tuning of fuzzy-neural weighting factors for a class of uncertain nonlinear systems based on the H∞ control technique and the strictly positive real Lyapunov (SPR-Lyapunov) design approach. The H∞-observer-based output feedback control law guarantees that all signals involved are bounded and provides the modeling error (and the external bounded disturbance) attenuation with H∞ performance, obtained by a Riccati-Like equation. Besides, the H∞-observer-based output feedback control law doesn't require the assumptions of the total system states available for measurement and the uncertain system nonlinearities only restricted to the system output. Finally, an example is simulated in order to confirm the effectiveness and applicability of the proposed methodsen_US
dc.description.urihttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=814133zh_TW
dc.identifierntnulib_tp_E0604_02_088zh_TW
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/32065
dc.languageenzh_TW
dc.relationIEEE International Conference on Systems, Man and Cybernetics, vol. 1, Tokyo,pp. 449-454en_US
dc.subject.otherFuzzy controlen_US
dc.subject.otherNeural networksen_US
dc.subject.otherNonlinear systemsen_US
dc.subject.otherAdaptive controlen_US
dc.subject.otherObserveren_US
dc.subject.otherHen_US
dc.subject.othercontrol.en_US
dc.titleH-inf.-observer-based adaptive fuzzy-neural control for a class of uncertain nonlinear systemsen_US

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