Novel Path Following for a Four-Wheel Steering Vehicle Based on Model Predictive Control

Zhang Bo, Rongqi Gu, Guang Chen

Abstract:

Path following is a crucial technique for ensuring
the safe and efficient operation of automatic electric vehicles.
Four-wheel steering (4WS) technology is known to enhance
the accuracy and flexibility of such vehicles. In this paper,
we propose a new constrained model predictive control (MPC)
based method for path-following, specifically for 4WS vehicles.
To simplify the 4WS vehicle kinematics model, we use the
assumption of pure rolling and simplify it to a single-track
model. We employ a high-precision linearization transformation
to convert the non-linear kinematics models to a linear control-
state system. Subsequently, we design a new objective function
based on the tracking error model, and formulate the control
problem as an optimization problem. Finally, we convert the
optimization problem into a quadratic programming (QP) form
with constraints that are suitable for real-time applications. We
demonstrate the effectiveness of our proposed control method
through simulation experiments.