Observer-Based Sliding Mode Control With Adaptive Event-Triggered Mechanism of Networked Discrete Singular Systems Against FDI Attacks

This work explores the core challenge of adaptive event-triggered sliding mode control (SMC) for networked discrete singular systems (NDSSs) in the presence of false data injection (FDI) attacks. This innovative adaptive event-triggered design draws inspiration from the median filtering technique to use the average values of current sampled output signal and the latest transmitted trigger signal as the trigger condition. By focusing on the instantaneous characteristics, the accuracy of the trigger judgment of the proposed adaptive event-triggered mechanism (AETM) is improved. Taking into account the false data injection attacks, a collaborative control method integrating the AETM and the observer-based sliding mode control is specifically formulated to utilize the robustness of sliding mode control to enhance the security and reliability of the NDSSs. By applying the singular value decomposition technique, fresh criteria for the NDSS to be regular, causal, and bounded are obtained based on linear matrix inequalities (LMIs). Furthermore, the finite-time convergence of the system trajectories to a region in the vicinity of the equilibrium point is guaranteed by the proposed SMC law. Ultimately, a direct current (DC) motor model and a tunnel diode circuit system simulations verify the effectiveness and practicality of the proposed method.