To enhance the safety of steer-by-wire (SbW) vehicles, a hierarchical vehicle stability control strategy consisting of an upper-level active front wheel steering (AFS) controller and a lower-level steering angle tracking controller is proposed. Firstly, in response to the parameter uncertainties and external disturbances in the vehicle dynamics model, a combination of linear quadratic regulator (LQR) optimal control, sliding mode control (SMC), and adaptive control techniques is employed to design an upper-level AFS controller based on adaptive robust optimization. This controller not only optimizes control objectives but also exhibits robust performance, ensuring the convergence of the actual side slip angle and yaw rate. Subsequently, a novel adaptive backstepping nonsingular fast terminal sliding mode (ABNFTSM) controller based on neural network approximator is designed in the lower-level to track the expected front wheel steering angle calculated in the upper-level. The fusion of Radial Basis Function Neural Networks (RBFNN) overcomes the dependence of traditional SMC on the upper bound of unknown functions. The designed controller provides high robustness, rapid transient response, and finite-time convergence, while retaining the global asymptotic stability of the backstepping control strategy based on Lyapunov criterion. Finally, the effectiveness and robustness of the proposed control strategy across various operating conditions are verified through three sets of simulation tests on the CarSim Simulink platform.
Wang et al. (Fri,) studied this question.