Observer-Based Direct Adaptive Fuzzy-Neural Control for Anti-lock Braking 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.authorG.-M. Chenen_US
dc.contributor.authorW.-Y. Wangen_US
dc.contributor.authorT.-T. Leeen_US
dc.contributor.authorC.-W. Taoen_US
dc.date.accessioned2014-10-30T09:28:14Z
dc.date.available2014-10-30T09:28:14Z
dc.date.issued2006-12-01zh_TW
dc.description.abstractIn this paper, an observer-based direct adaptive fuzzy-neural controller (ODAFNC) for an anti-lock braking system (ABS) is developed under the constraint that only the system output, i.e., the wheel slip ratio, is measurable. The main control strategy is to force the wheel slip ratio to well track the optimal value, which may vary with the environment. The observer-based output feedback control law and update law for on-line tuning of the weighting factors of the direct adaptive fuzzy-neural controller are derived. By using the strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be guaranteed. Simulation results demonstrate the effectiveness of the proposed control scheme forABS control.en_US
dc.description.urihttp://www.ijfs.org.tw/ePublication/2006_paper_4/05%20IJFS_ABS%20.pdfzh_TW
dc.identifierntnulib_tp_E0604_01_028zh_TW
dc.identifier.issn1562-2479zh_TW
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/31950
dc.languageenzh_TW
dc.publisher中華民國模糊學會zh_tw
dc.relationInternational Journal of Fuzzy Systems, 8(4), 208-218.en_US
dc.subject.otheranti-lock braking systemen_US
dc.subject.otherslip ratioen_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.titleObserver-Based Direct Adaptive Fuzzy-Neural Control for Anti-lock Braking Systemsen_US

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