Please use this identifier to cite or link to this item: http://rportal.lib.ntnu.edu.tw:80/handle/77345300/31950
Title: Observer-Based Direct Adaptive Fuzzy-Neural Control for Anti-lock Braking Systems
Authors: 國立臺灣師範大學電機工程學系
G.-M. Chen
W.-Y. Wang
T.-T. Lee
C.-W. Tao
Issue Date: 1-Dec-2006
Publisher: 中華民國模糊學會
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.
URI: http://rportal.lib.ntnu.edu.tw/handle/77345300/31950
ISSN: 1562-2479
Other Identifiers: ntnulib_tp_E0604_01_028
Appears in Collections:教師著作

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