Co-Predictor-Based Resilient Control of Nonlinear Load Frequency Control Systems Under FDI Attacks and Large Delays

This article proposes a co-predictor-based load frequency control (LFC) strategy for wind power systems (WPSs) subject to time-varying uncertainties, large input delays, and false data injection attacks (FDIAs). ATakagi-Sugeno (T-S) fuzzy model is utilized to characterize the nonlinear dynamics of the WPS, effectively capturing both operational fluctuations and the compounded impact of communication delays and cyber attacks. To circumvent the challenges posed by large delays, a sequential co-predictor cascade framework featuring a collaborative state-attack prediction mechanism is developed. This hierarchical architecture partitions the total delay into manageable subintervals, facilitating stepwise prediction of system states and FDIA signals based solely on output measurements. Furthermore, a unified co-design approach for fuzzy control laws and subpredictor gains is established to guarantee the stability of the closed-loop system. Extensive simulations across various scenarios validate the efficacy of the proposed method, highlighting its superiority in enhancing frequency stability and cyber-resilience.