Dynamic event-triggered fuzzy control of DC microgrids under FDI attacks and imperfect premise matching

Abstract

This paper investigates the T–S fuzzy control of DC microgrids subject to false data injection (FDI) attacks, premise mismatching, and network delays using a dynamic event-triggered mechanism (ETM). Unlike the static ETMs using the fixed triggering parameters, by adaptively adjusting the triggering parameters, the proposed novel discrete-time dynamic ETM can more effectively reduce excessive usage of communication resources, and the Zeno behavior is also avoided naturally. Then, a novel T–S fuzzy closed-loop system model is built, which considers the FDI attacks, dynamic ETM, delays and premise mismatching all in one unified framework. Mean-square exponential stability criteria are derived, which establish the relationship between system performance and the contributing factors. Further, unlike the two-step emulation based method, the proposed co-design method can design the injection current controller and the dynamic ETM in one step, which offers a convenient framework for the tradeoffs between control and communication performances. Both simulation and experimental results confirm the effectiveness of the proposed methods, achieving 27.5% savings of communication resources while effectively stabilizing the DC microgrid even under the situation that 13.5% of the transmitted data are tampered by the FDI attacks.