Dynamic Slip-Ratio Estimation and Control of Antilock Braking Systems Using an Observer-Based Direct Adaptive Fuzzy-Neural Controller

被引：74

作者：

Wang, Wei-Yen ^{[1
]}

Li, I-Hum ^{[2
]}

Chen, Ming-Chang ^{[3
]}

Su, Shun-Feng ^{[3
]}

Hsu, Shi-Boun ^{[4
]}

机构：

[1] Natl Taiwan Normal Univ, Dept Appl Elect Technol, Taipei 106, Taiwan

[2] Lee Ming Inst Technol, Dept Comp Sci & Informat Engn, Taipei 243, Taiwan

[3] Natl Taiwan Univ Sci & Technol, Dept Elect Engn, Taipei 106, Taiwan

[4] Mstar Semicond Co, Hsinchu 302, Taiwan

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2009年 / 56卷 / 05期

关键词：

Antilock braking systems (ABSs); observer-based direct adaptive fuzzy-neural controller (DAFC); road estimators; HYBRID ELECTRIC VEHICLES; SIMULATION; DRIVEN; ROBUST; FRONT;

D O I：

10.1109/TIE.2008.2009439

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：1746 / 1756

页数：11

共 25 条

[11]

He XL, 2002, IEEE T INTELL TRANSP, V3, P235, DOI 10.1109/TITS.2002.807781

[12] Future vehicle driven by electricity and control - Research on four-wheel-motored "UOT Electric March II [J].

Hori, Y .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2004, 51 (05) :954-962

[13]

KAWABE T, 1995, P 35 C DEC CONTR KOB, P2769

[14] Application of fuzzy control algorithms for electric vehicle antilock braking/traction control systems [J].

Khatun, P ;

Bingham, CM ;

Schofield, N ;

Mellor, PH .

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2003, 52 (05) :1356-1364

[15]

Lee Y, 2001, P AMER CONTR CONF, P671, DOI 10.1109/ACC.2001.945791

[16] Observer-based adaptive fuzzy-neural control for unknown nonlinear dynamical systems [J].

Leu, YG ;

Lee, TT ;

Wang, WY .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1999, 29 (05) :583-591

[17] Observer-based direct adaptive fuzzy-neural control for nonaffine nonlinear systems [J].

Leu, YG ;

Wang, WY ;

Lee, TT .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2005, 16 (04) :853-861

[18] Improved hybrid particle swarm optimized wavelet neural network for Modeling the development of Fluid Dispensing for Electronic Packaging [J].

Ling, S. H. ;

Iu, H. H. C. ;

Leung, F. H. F. ;

Chan, K. Y. .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2008, 55 (09) :3447-3460

[19] A FUZZY-LOGIC CONTROLLER FOR AN ABS BRAKING SYSTEM [J].

MAUER, GF .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1995, 3 (04) :381-388

[20] Electric braking control methods for electric vehicles with independently driven front and rear wheels [J].

Mutoh, Nobuyoshi ;

Hayano, Yuichi ;

Yahagi, Hiromichi ;

Takita, Kazuya .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2007, 54 (02) :1168-1176

← 1 2 3 →