Position Control Considering Slip Motion of Tracked Vehicle Using Driving Force Distribution and Lateral Disturbance Suppression

Abstract

Complex slippage and nonholonomic constraints can disturb the precise movement of tracked vehicles. In this study, a position control system using driving force control and virtual-turning velocity control (VTVC) was established for a tracked vehicle. Slippage in the translational direction can be suppressed by controlling the driving force of the crawlers, estimated using the vehicle velocity. However, the driving forces interfere with each other in a turning motion. Therefore, a driving force distribution method was developed using the instantaneous turning center of a vehicle to decouple the forces. This distribution induced slippage in the direction of turning. In addition, a virtual reference was derived from the vehicle velocity and lateral disturbance, which described the effects of the nonholonomic constraints and skidding of the tracked vehicle. Next, a VTVC method was developed to suppress the lateral disturbance by controlling the turning velocity to follow the virtual reference. The experimental results confirm that the proposed approach ensures high-performance position tracking and adequate slippage of the tracked vehicle.

Keywords

• Autonomous vehicles
• driving force control
• machine learning
• observers
• position control