Adaptive Path Tracking for Multi-Axle Vehicles with Integrated All-Wheel Steering Control

Multi-axle vehicles offer strong load capacity and driving stability, while all-wheel steering (AWS) improves their maneuverability and Control stability. However, coordinating multiple steering axles while balancing flexibility and stability remains a challenge in path tracking control. This paper proposes a novel control framework that integrates AWS into the path tracking process of multi-axle vehicles. A nonlinear model predictive controller (NMPC) is developed to optimize tracking performance, incorporating kinematic and dynamic objective functions that explicitly regulate front and rear wheel steering angles. This integration enables coordination of axle angles based on path tracking demands. Additionally, an adaptive weighting mechanism is introduced, in which the adjustment coefficients vary according to the vehicle's stability domain boundary to dynamically tune the control strategy under different operating conditions. Simulation results demonstrate that the proposed method significantly enhances both flexibility and stability in various driving scenarios, validating its effectiveness for complex maneuvering tasks.