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Because autonomous vehicles (AVs) equipped with active front steering have the features of time varying, uncertainties, high rate of fault, and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving lateral stability in steer-by-wire (SBW) vehicles in the presence of abrupt nonlinear faults. First, an upper-level robust H∞ controller is designed to obtain the desired front-wheel steering angle for driving both the yaw rate and the sideslip angle to reach their correct values. Takagi-Sugeno (T-S) fuzzy modeling method, which has shown the extraordinary ability in coping with the issue of nonlinear, is applied to deal with the challenge of the changing longitudinal velocity. The output of the upper controller can be calculated by a parallel distributed compensation (PDC) scheme.

For the improvement of the vehicle yaw stability, this paper studies the control problem of the active front steering (AFS) system with actuator input delay. A novel sliding mode predictive control method to handle actuator input delay is proposed for the AFS system. Firstly, considering the nonlinearities of the vehicle system, a linear parameter varying vehicle system model with two-level structure is proposed to capture the vehicle dynamic behaviors. Secondly, to deal with the issues of actuator input delay and system constraints, a novel sliding mode predictive control method is put forward. In the process of controller design, a sliding mode control algorithm is employed for the improvement of the robustness of the control system, and then a model predictive control algorithm is employed to deal with system constraints.