Abstract:
A neural network (NN) adaptive model-based combined
lateral and longitudinal vehicle control algorithm for
highway applications is presented in this paper. The controller
is synthesized using a proportional plus derivative control coupled
with an online adaptive neural module that acts as a dynamic
compensator to counteract inherent model discrepancies,
strong nonlinearities, and coupling effects. The closed-loop stability
issues of this combined control scheme are analyzed using a
Lyapunov-based method. The neurocontrol approach can guarantee
the uniform ultimate bounds of the tracking errors and
bounds of NN weights. A complex nonlinear three-degreeof-
freedom dynamic model of a passenger wagon is developed to
simulate the vehicle motion and for controller design. The controller
is tested and verified via computer simulations in the presence
of parametric uncertainties and severe driving conditions
