T-S fuzzy fault-tolerant load frequency control for power systems with energy storage system under DoS attacks and actuator failures: A two-step adaptive event-triggered mechanism

This research focuses on the T-S fuzzy non-fragile fault-tolerant load frequency control (FTLFC) problem in power systems with energy storage system (ESS), considering the coexistence of DoS attacks and local actuator failures. Firstly, a random distribution model is constructed based on the distribution characteristics of actuator local failures to accurately characterize the uncertainty of the fault behavior. Considering the scarcity of network bandwidth resources, this study introduces an innovative two-step adaptive event-triggered mechanism (TSAETM), significantly improving data transmission efficiency and reducing network load by intelligently screening and transmitting crucial data packets. Furthermore, to enhance the accuracy and robustness of the system state monitoring, a flexible switched observer framework is designed, which can adapt to the dynamic changes of the system and provide more accurate state estimation. Subsequently, advanced segmental Lyapunov functional analysis methods, combined with linear matrix inequality (LMI) techniques, are employed to rigorously demonstrate that the closed-loop switched system (CLSS) can maintain global exponential stability (GES) and exhibit the ideal $H_{\infty }$ performance when subjected to DoS attacks and actuator failures. Finally, the effectiveness of the proposed scheme is comprehensively verified through simulation experiments.