A Neural Network Technique for Automatic Steering Control of a Highway Rotary Snow Blower Vehicle

In this paper, a neural network technique for automatic steering control of a highway rotary snow blower vehicle is presented. The technique is introduced to improve the performance of the lateral position tracking control of the vehicle. First, Proportional-Derivative (PD) controllers (one for position, one for heading angle) are developed from the bicycle model of the vehicle to control the steering angle to follow the desired trajectory. Then a neural network controller is added to compensate for uncertainties in vehicle dynamics. Simulation studies of the neural control technique are conducted for the rotary snow blower vehicle model under virtual snow blowing conditions.