Multi-source motion constrained model predictive control for tractor-trailer trucks with coupled dynamics

Abstract

This paper proposes a constrained model predictive control (MPC) for tractor-trailer trucks with the complicated physical characteristics, where motion constraints can be considered to govern the vehicle maneuver. Firstly, a targeted theoretical derivation method is developed to establish a more accurate nonlinear model for articulated vehicles, with expressly considering the articulation coupling effects. As an essential basis, the kinematic coupling behavior is further investigated. Secondly, multi-source motion constraints are introduced in particular with the analysis of nonholonomic constraints on the underactuated trailer: (i) keeping trucks traveling in the feasible domain away from collision; (ii) maintaining the vehicle states in a stable field through the steady-state response and side-slip thresholds. Thirdly, a constrained MPC controller is constructed for the automatic tracking operation, wherein vehicle demands of position security and yaw stability will be taken into reasonable consideration. For this purpose, vehicle states information can be fully utilized in a parallel approach to optimize quadratic programming (QP) in MPC: model prediction and updated constraints. In the end, the contrasted-simulation analysis is carried out to verify the accuracy of derived model and effectiveness of the designed controller, along with the feasibility of the additive multi-source constraints.