On-Line Adaptive T-S Fuzzy Neural Control for Active Suspension Systems

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.authorM.-C. Chenen_US
dc.contributor.authorY.-H. Chienen_US
dc.contributor.authorT.-T. Leeen_US
dc.date.accessioned2014-10-30T09:28:19Z
dc.date.available2014-10-30T09:28:19Z
dc.date.issued2009-08-24zh_TW
dc.description.abstractVehicles are not always driven on smooth roads. If parts of the suspension system fail, it becomes an uncertain system. Thus we need an approximator to remodel this uncertain system to maintain good control. In this paper, we propose a new method to on-line identify the uncertain suspension system and design a T-S fuzzy-neural controller to control it. We first use the mean value theorem to transform the active suspension system into a virtual linearized system. In addition, an on-line adaptive T-S fuzzy-neural modeling approach to the design of robust tracking controllers is developed for the uncertain active suspension system. Finally, this paper gives simulation results of an uncertain suspension system with the on-line adaptive T-S fuzzy-neural controller, and is shown to provide good effectiveness under the conditions that parts of the suspension system fail.en_US
dc.description.urihttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5277406zh_TW
dc.identifierntnulib_tp_E0604_02_022zh_TW
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/31999
dc.languageenzh_TW
dc.relationIEEE International Conference on Fuzzy Systems,orea,pp.1297-1302en_US
dc.titleOn-Line Adaptive T-S Fuzzy Neural Control for Active Suspension Systemsen_US

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