Event-Triggered Fault Estimation and Fault Tolerance for Cyber-Physical Systems with False Data Injection Attacks

This paper investigates an event-triggered framework for addressing fault estimation and fault tolerance issues in discrete-time cyber-physical systems (CPSs) with partial state saturations and random false data injection attacks (FDIAs). A stochastic variable is introduced to characterize the random FDIAs and to establish the corresponding model. A reduced-order fault estimator and an event condition are co-derived to reconstruct system states and actuator faults. The proposed event-triggered transmission scheme helps reduce network utilization in the sensor-to-estimator channel. A sufficient condition for the proposed event-triggered estimator is derived, which minimizes state and fault estimation errors even when the controlled plants are subject to exogenous disturbances, fault signals, and random attacks. Furthermore, a fault-tolerant compensation controller is proposed using the estimated states and faults, ensuring that the considered systems achieve mean-squared stability. Finally, a DC motor platform is developed to further demonstrate the effectiveness of the designed estimator-based fault-tolerant controller.