TY - JOUR
T1 - Dynamic slip-ratio estimation and control of antilock braking systems using an observer-based direct adaptive fuzzy-neural controller
AU - Wang, Wei Yen
AU - Li, I. Hsum
AU - Chen, Ming Chang
AU - Su, Shun Feng
AU - Hsu, Shi Boun
N1 - Funding Information:
Manuscript received January 12, 2006; revised March 20, 2007 and July 17, 2008. First published November 18, 2008; current version published April 29, 2009. This work was supported by the National Science Council, Taiwan, under Grant NSC 94-2213-E-030-011. W.-Y. Wang is with the Department of Applied Electronics Technology, National Taiwan Normal University, Taipei 106, Taiwan (e-mail: wywang@ntnu. edu.tw). I-H. Li is with the Department of Computer Science and Information Engineering, Lee-Ming Institute of Technology, Taipei 243, Taiwan (e-mail: [email protected]). M.-C. Chen is with the Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan (e-mail: [email protected]). S.-F. Su is with the Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan. S.-B. Hsu is with the Mstar Semiconductor Company, Hsinchu 302, Taiwan. Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TIE.2008.2009439
PY - 2009
Y1 - 2009
N2 - This paper proposes an antilock braking system (ABS), in which unknown road characteristics are resolved by a road estimator. This estimator is based on the LuGre friction model with a road condition parameter and can transmit a reference slip ratio to a slip-ratio controller through a mapping function. The slip-ratio controller is used to maintain the slip ratio of the wheel at the reference values for various road surfaces. In the controller design, an observer-based direct adaptive fuzzy-neural controller (DAFC) for an ABS is developed to online-tune the weighting factors of the controller under the assumption that only the wheel slip ratio is available. Finally, this paper gives simulation results of an ABS with the road estimator and the DAFC, which are shown to provide good effectiveness under varying road conditions.
AB - This paper proposes an antilock braking system (ABS), in which unknown road characteristics are resolved by a road estimator. This estimator is based on the LuGre friction model with a road condition parameter and can transmit a reference slip ratio to a slip-ratio controller through a mapping function. The slip-ratio controller is used to maintain the slip ratio of the wheel at the reference values for various road surfaces. In the controller design, an observer-based direct adaptive fuzzy-neural controller (DAFC) for an ABS is developed to online-tune the weighting factors of the controller under the assumption that only the wheel slip ratio is available. Finally, this paper gives simulation results of an ABS with the road estimator and the DAFC, which are shown to provide good effectiveness under varying road conditions.
KW - Antilock braking systems
KW - Antilock braking systems (ABSs)
KW - Observer-based direct adaptive fuzzy - neural controller (DAFC)
KW - Observer-based direct adaptive fuzzy-neural controller
KW - Road estimators
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U2 - 10.1109/TIE.2008.2009439
DO - 10.1109/TIE.2008.2009439
M3 - Article
AN - SCOPUS:66149093151
SN - 0278-0046
VL - 56
SP - 1746
EP - 1756
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 5
ER -