Adaptive Event-Triggered Fuzzy Security Control for Active Suspensions of In-Wheel-Motor-Driven Electric Vehicles With Probabilistic Actuator Attacks

To improve vibration performances and save network resources for the active suspension systems (ASSs) of in-wheel-motor-driven vehicles (IWMDVs), this article proposes an adaptive event-triggered fuzzy security control method with consideration of probabilistic actuator attacks. First, to describe the nonlinear dynamic behaviors of spring and damper in the suspension systems, an interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy suspension model is constructed with a dynamic vibration absorber (DVA). Second, to avoid unnecessary transmission of sampled data, an adaptive event-triggered communication (ETC) scheme is developed to regulate the transmission of sampled data and improve the utilization of network resources. Third, a security controller design condition is derived to ensure that the active suspension satisfies the asymptotic stability as well as the vibration suppression performance, despite the occurrence of probabilistic actuator attacks. Finally, the simulation and experimental results verified the superiority of the proposed method in terms of improving ride comfort and enhancing network resource efficiency, as compared with the current suspension control methods.