Adaptive quantized control for high-order fully actuated strict-feedback systems against multiple false data injection attacks

This paper primarily focuses on developing a concise and direct adaptive asymptotic control strategy for input-quantized high-order fully actuated strict-feedback systems, with the objective of mitigating the detrimental effects induced by stealthy multiple false data injection attacks. As each sensor is corrupted by ill-disposed hackers, the exact full-state measurements are unavailable for controller design. After theoretical deductions, the initial issues of false data injection attacks and input quantification are converted into multiple unknown control directions and lumped uncertainty dynamics. By incorporating positive integral time-varying functions into the command filters and adaptive controller, the Nussbaum function-based asymptotic tracking control is formulated. To conclude, numerical simulations are conducted to verify the effectiveness of the proposed control framework.