Security enhancement of nonlinear networked systems under stochastic cyber-attack using fuzzy event-triggered control

This paper proposes a resilient distributed event-triggered (ET) control framework for nonlinear networked control systems (NCSs) modelled via the Takagi–Sugeno (T-S) fuzzy approach under stochastic cyber-attacks. Unlike conventional centralised ET strategies, the proposed scheme adopts a fully decentralised triggering mechanism in which each sensor independently determines its transmission instants. This design not only alleviates communication congestion and reduces energy consumption but also provides scalability to large-scale interconnected systems. To accurately capture adversarial behaviours, a novel modelling framework is developed that simultaneously incorporates two distinct classes of nonlinear cyber-attacks reflecting more realistic and compounded threat scenarios. By embedding these attacks into the control design, the proposed scheme strengthens system resilience against compounded adversarial scenarios. Rigorous stability conditions are derived through Lyapunov theory and formulated in terms of linear matrix inequalities (LMIs), ensuring stability of the closed-loop system. The effectiveness of the proposed framework is validated on a mass spring system through both numerical simulations and real-time experimental tests, demonstrating its ability to preserve stability and security of the closed-loop system under adverse cyber-attack scenarios.