Stable anti-lock braking system using output-feedback direct adaptive fuzzy neural control

Wei Yen Wang, Guan Ming Chen, C. W. Tao

研究成果: 雜誌貢獻Conference article

12 引文 斯高帕斯(Scopus)

摘要

In this paper, an output-feedback direct adaptive fuzzy neural controller for an anti-lock braking system (ABS) is developed. It is assumed that only the system output, the wheel slip ratio, is available for measurement. The main control strategy is to force the wheel slip ratio tracking variant optimal slip ratios, which may vary with the environment and assumed to be known during the vehicle-stopping period. By using the strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be verified. To demonstrate the effectiveness of the proposed method, simulation results are illustrated.

原文英語
頁(從 - 到)3675-3680
頁數6
期刊Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
4
出版狀態已發佈 - 2003 十一月 24
事件System Security and Assurance - Washington, DC, 美国
持續時間: 2003 十月 52003 十月 8

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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