A Genetic Algorithm-Assisted Fault Detection Observer for Networked Systems Under Denial-of-Service Attacks

This work solves the issue of event-triggered fault detection for networked systems under the denial-of-service (DoS) attacks. To improve the utilization rate of network resources, an event-triggered mechanism is employed to reduce the transmission frequency. A fault detection observer is designed to generate the residual signal for the concerned system with external disturbances and faults. Note that the input signal of the fault detection observer (FDO) transmitted over a communication network is assumed to be vulnerable to cyber attacks, in which the adversaries may interrupt the transmission process. The
${\mathcal {H}}_\infty$
attenuation index and
${\mathcal {H}}_{\_}$
increscent index are introduced into the fault detection observer design, which reflects the robustness to external disturbances and sensitivity to faults, respectively. By applying the Lyapunov functional technology, some nonlinear matrix inequalities are acquired to guarantee the existence of the fault detection observer with the appearance of DoS attacks. Then, a genetic algorithm is adopted to cope with the derived nonlinear matrix inequalities without introducing any conservatism. The simulation results related to an unmanned aerial vehicle model are presented to illustrate the correctness and effectiveness of the presented fault detection strategy.