State Estimation for Reaction–Diffusion Genetic Regulatory Networks Via Resilient Event‐Triggered Protocol

ABSTRACT This paper studies the event‐triggered state estimation problem of reaction–diffusion genetic regulatory networks (RDGRNs) under denial‐of‐service (DoS) attacks and spatially local averaged measurements (SLAMs). The output states of mRNA and protein under SLAMs are only time‐dependent, and the distribution of sensors in space is effectively reduced, which is more practical. A resilient event‐triggered strategy is proposed to compensate for the malicious effects of intermittent DoS attacks and improve communication resource utilization. We serve the output states under SLAMs as the trigger condition, which eliminates the need for spatial integration, making the triggering process more straightforward. Furthermore, we construct a novel piecewise Lyapunov–Krasovskii functional to ensure that the error system is stable. In addition, the gain matrices of the state estimator are given by solving linear matrix inequalities. Finally, a simulation example is presented to demonstrate the feasibility of the obtained results.