<p>This paper addresses the tracking control problem of intelligent vehicle steering systems with actuator faults and model uncertainty. An adaptive fuzzy logic system is employed to online approximate the unmodeled nonlinear dynamics of the steering system, which is combined with dynamic gain technology to design an adaptive sliding mode controller. This controller effectively compensates for the influences of unknown control gain and actuator faults on control performance. To mitigate the chattering phenomenon inherent in sliding mode control, first-order filtering technology is integrated into the controller design, ensuring smooth system operation. Finally, the designed controller can realize the asymptotic stability of the intelligent vehicle steering system by combining Lyapunov stability theorem analysis. The rationality of the designed control method is verified by numerical simulation and vehicle experiments.</p>