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.
Mathematics Subject Classification: 92B20, 93C10.