Work

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

Year: 2021

Type: article

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$\mathcal {H}_{\infty }$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.

Source: IEEE Transactions on Network Science and Engineering

DOI: 10.1109/tnse.2021.3121727

Authors: Xiang-Gui Guo, Dong-Yu Zhang, Jian-Liang Wang, Ju H. Park, Lei Guo

Institutions: University of Science and Technology Beijing, Beihang University, Yeungnam University

Language: English

Topic: Distributed Control Multi-Agent Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,045