Journal of Northeastern University(Natural Science)

Journal of Northeastern University ›› 2009, Vol. 30 ›› Issue (3): 309-312.DOI: -

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Slip controller based on RBF neural network for automotive ABS

Mao, Yan-E (1); Jing, Yuan-Wei (1); Cao, Yi-Peng (2); Zhang, Si-Ying (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China; (2) School of Computer Science, Shenyang Institute of Aeronautical Engineering, Shenyang 110136, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-03-15 Published:2013-06-22
  • Contact: Mao, Y.-E.
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Abstract: The slip controller based on RBF neural network was designed for automotive anti-lock braking system (ABS) to meet the requirements that the braking process should be fast and robust and the chattering due to conventional slip control should be alleviated as possible. Moreover, the robustness of adaptive control system simply based on neural network can be improved to some extent if using the slip controller we designed. The simulation using the software MATLAB/SIMULINK was done to investigate vehicles' braking effects on dry road pavement, thus verifying the effectiveness and feasibility of the control scheme proposed.

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