Integrated Path Tracking Controller of Underground Articulated Vehicle Based on Nonlinear Model Predictive Control

Abstract

This paper proposes an integrated path tracking controller for articulated vehicles. A nonlinear model-predictive control (NMPC)-based reference state tracker is designed as an upper-level controller to solve the vehicle’s longitudinal velocity and steering rate. A terminal cost is introduced into the NMPC to improve the controller’s stability. A lower-level controller is developed to translate upper-level solutions into vehicle actuators’ signals, including steering and driving controllers. The steering controller translates the steering rate into the linear velocity of the cylinder to calculate the required fluid volume and ultimately into the rotation speed of the steering motor. The neural network method is applied in the driving controller to ensure accuracy under different loadings. In order to investigate the effects of the path tracking controller, an articulated dump truck is adapted for the field tests by adding the steering-by-wire system and driving-by-wire system, respectively. Experimental verifications of the lower-level controller are performed. The results show that the controller can accurately satisfy the demand. Finally, the tracking performance of the integrated path tracking controller is analyzed experimentally under different reference velocities. The results indicate that tracking accuracy can be guaranteed.