Traction Control of an Inverted Pendulum Robotic Vehicle Based on a Driving Wheel Motion Model

Abstract

This paper presents a traction control method for an inverted pendulum self-balancing robotic vehicle aimed at maintaining postural stability on low friction surfaces by preventing unexpected wheel slip. The maximum transmissible torque (MTT) estimation method allows for the traction force of a wheel to be sustained by restricting the overall control input to the MTT in real time. However, the anti-slip performance is heavily dependent on the accuracy of the dynamic model of driving wheels. To address this issue, we first incorporate the coupling effect of the inverted pendulum into the longitudinal motion model. Next, a nonlinear disturbance observer is implemented to compensate for model uncertainty due to unknown surface conditions. Comparative simulations demonstrate that the proposed traction control method significantly enhances the stability of the self-balancing vehicle, which greatly reduces the likelihood of fall-overs, especially when the balancing robot is operating on slippery flat surfaces or unknown slopes.