April  1999, 5(2): 321-338. doi: 10.3934/dcds.1999.5.321

A neural network based anti-skid brake system

1. 

Department of Electrical & Electronic Engineering, University of Adelaide, South Australia 5005, Australia, Australia

Received  October 1997 Revised  December 1998 Published  January 1999

The novel application of a neural network based adaptive control scheme to an anti-skid brake system (ABS) is presented in this paper. The anti-skid brake system represents a unique and challenging application for neural network based control schemes. The principal benefit of using neural networks in anti-skid brake systems is their ability to adapt to changes in the environmental conditions without a significant degradation in performance. In the proposed approach, the controller neural network is designed to produce a braking torque which regulates the wheel slip for the vehicle-brake system to a prespecified level. An enhanced reference model is proposed which generates the desired slip response and enables a sufficient condition for the convergence of the tracking error to be derived. Simulation studies are performed to demonstrate the effectiveness of the proposed neural network based anti-skid brake system (NN-ABS) for various road surface conditions, inclines in the road, and transition between road surfaces.
Citation: Sanjay K. Mazumdar, Cheng-Chew Lim. A neural network based anti-skid brake system. Discrete & Continuous Dynamical Systems - A, 1999, 5 (2) : 321-338. doi: 10.3934/dcds.1999.5.321
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