Resilient frequency control of renewable shipboard microgrids under false data injection attacks using adaptive nonsingular terminal fractional-order sliding mode control

Due to the aim of decreasing dependence on fossil fuels and pollution concerns, renewable energy penetration in marine power systems is rapidly increasing. However, this transition requires advanced automated infrastructures for reliable frequency regulation in shipboard microgrids. Renewable generation sources and load variations, modelling uncertainties, and vulnerability to cyberattacks due to the use of Industry 4.0 technologies are critical challenges for reliable frequency regulation. To address these challenges, this paper develops a fractional-order control framework for shipboard microgrids. The proposed controller utilises an adaptive fuzzy estimator, fractional-order sliding-mode control, and an adaptive barrier function. A component-wise fractional-order SMG model adopted from previous studies is used as a control-oriented representation of heterogeneous, memory-dependent, and multi-time-scale dynamics. In the proposed strategy, actuator-side false data injection attacks are handled through the robustness of the sliding mode structure. External disturbances and uncertainty effects are compensated by an adaptive term. An adaptive fuzzy estimator is also introduced to approximate lumped uncertainties online. This improves control precision under changing operating conditions. The barrier function and fuzzy mechanism help reduce chattering and suppress oscillations, leading to smoother control action. Moreover, controller parameters are tuned to improve robustness and speed up frequency recovery. Simulations and Speedgoat hardware-in-the-loop tests under wind, solar, wave, and load disturbances show faster settling, lower overshoot, stronger resilience, and better real-time performance than conventional controllers.