This paper investigates the secure lateral stabilization control problem of autonomous vehicles subject to actuator attacks. By considering a class of arbitrary bounded actuator attacks, a secure lateral control model of autonomous vehicles is established to characterize the influences of actuator attacks on steer actions. Based on the established attacked model, the event-based transmission scheme is used to save communication resources, and the sliding-model-like control scheme is developed to counteract the effects of actuator attacks. By exploiting the input delay approach, the periodic sampling and network-induced time delay are considered and thus the provided secure control scheme is beneficial to realize the secure control under networked environment. All theory results are well derived by Lyapunov–Kraskovskii method and some linear matrix inequality operations. In addition, Zeno behaviors are naturally excluded due to the adoption of discrete-time period sampling fashion. The effectiveness of the proposed secure control scheme is verified by a comparative simulation example.
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