A Zonotopic Secure Estimation Framework for Cyber–Physical Systems Under Dynamic Event-Triggered Mechanism

This paper proposes a zonotopic secure estimation framework for discrete-time cyber-physical systems (CPSs) subject to unknown-but-bounded (UBB) disturbances and false data injection (FDI) attacks. A decentralized dynamic event-triggered mechanism (DETM) is developed, allowing each sensor to adapt its triggering threshold using local output deviations, thereby reducing communication while preserving estimation accuracy. Subsequently, a zonotopic interval observer is developed to estimate the system state under DETM. The observer propagates zonotopic error bounds and is designed via LMIs to ensure stability and l1 performance. Furthermore, a zonotope-based attack reconstruction approach is formulated. The attack signal is conservatively enclosed in a residual-based zonotope, and a threshold test is used to isolate attacked channels. Finally, simulation results confirm that the method reduces communication significantly while maintaining reliable estimation, validating its use in resource-constrained CPSs.