Autonomous Circular Drift Control for 4WD-4WS Vehicles Without Precomputed Drifting Equilibrium
Yue Xiao, Yi He, Yaqing Zhang, Xin Lin, Ming Zhang
TL;DR
This work addresses drifting control for autonomous $4WD-4WS$ vehicles without relying on precomputed drift equilibria. It proposes a two-layer hierarchical controller: an upper-layer MPC for trajectory tracking and a lower-layer inverse tire model solved by Newton-Raphson to produce steering angles and motor torques, with a simplified 3DoF bicycle dynamic framework and a Magic Tire Formula for lateral forces, $F_{yf}=\mu F_{zf}\sin(C\arctan(B\alpha_f))$, integrated into a robust MPC via an octagonal friction-circle approximation. A yaw-rate command is enhanced to drive drift through a feedback term, and error compensation with a bounded disturbance $d_k$ and a low-pass correction reduces steady-state errors, yielding a robust control framework. MATLAB/Simulink and CarSim simulations on constant- and variable-curvature circles show accurate tracking and sustained drift, highlighting the benefits of distributing forces across all four tires in a 4WD-4WS system and the practicality of the approach for high-friction or hazardous scenarios.
Abstract
Under extreme conditions, autonomous drifting enables vehicles to follow predefined paths at large slip angles, significantly enhancing the control system's capability to handle hazardous scenarios. Four-wheel-drive and four-wheel-steering (4WD-4WS) vehicles, which have been extensively studied, offer superior path-following precision and enhanced maneuverability under challenging driving conditions. In this paper, a hierarchical drifting controller is proposed for 4WD-4WS vehicles to track both path and velocity without relying on precomputed drifting equilibrium. The controller is structured into two layers: a trajectory tracking layer and an actuator regulation layer. The first layer generates the desired tire forces in the vehicle body frame, while the second layer converts these desired tire forces into steering angle commands and torque commands for the front and rear motors. The effectiveness and robustness of the proposed controller are validated through simulation.