Observer-Based Direct Adaptive Fuzzy-Neural Control for Anti-lock Braking Systems

dc.contributor 國立臺灣師範大學電機工程學系 zh_tw G.-M. Chen en_US W.-Y. Wang en_US T.-T. Lee en_US C.-W. Tao en_US 2014-10-30T09:28:14Z 2014-10-30T09:28:14Z 2006-12-01 zh_TW
dc.description.abstract In 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.uri zh_TW
dc.identifier ntnulib_tp_E0604_01_028 zh_TW
dc.identifier.issn 1562-2479 zh_TW
dc.language en zh_TW
dc.publisher 中華民國模糊學會 zh_tw
dc.relation International Journal of Fuzzy Systems, 8(4), 208-218. en_US
dc.subject.other anti-lock braking system en_US
dc.subject.other slip ratio en_US
dc.subject.other fuzzy control en_US
dc.subject.other neural networks en_US
dc.subject.other nonlinear systems en_US
dc.subject.other adaptive control en_US
dc.subject.other observer en_US
dc.title Observer-Based Direct Adaptive Fuzzy-Neural Control for Anti-lock Braking Systems en_US