Event-Triggered Observer-Based $\mathcal {H}_\infty$ Consensus Control and Fault Detection of Multiagent Systems Under Stochastic False Data Injection Attacks

Abstract

This paper investigates the event-triggered observer-based security consensus and fault detection problem for nonlinear multi-agent systems (MASs) under external disturbances and stochastic false data injection attacks (FDIAs) over a directed communication network. The randomly occurring FDIAs are modeled by random variables that follow the Bernoulli distribution. An observer-based event-triggered control strategy using only local measurements and information from neighboring agents is developed, where the Zeno behavior of event-triggered mechanism (ETM) is excluded. Interestingly, the observer errors are first regarded as disturbance and then attenuated by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {H}_{\infty }$</tex-math></inline-formula> norm bounds, together with the external disturbances. Meanwhile, it is worth highlighting here that the same information used by the state observers is also adopted to construct residuals with adaptive thresholds, whose aim is to detect faults occurring in any agents. In addition, the accuracy of the observer and the performance of the fault detection mechanism are improved by introducing the disturbance compensation mechanism. Finally, simulation results are provided to illustrate the effectiveness and advantages of the proposed strategy.