An Adaptive Fixed-Time Dynamic Triggered Control for Interconnected Power Systems Under Denial-of-Service Attacks

In this work, an adaptive fixed-time dynamic triggered control issue for interconnected power systems under Denial-of-Service (DoS) attacks is investigated. Such attacks would impede the transmission of sensor signals in interconnected power systems, precipitating a severely unstable power supply or even paralysis. To effectively confront this challenge, an adaptive switching neural network state observer is designed. The observer can maintain the output of the observation state under both attack conditions and normal conditions, thereby compensating for the adverse effects of DoS attacks on interconnected power systems. Meanwhile, a nonlinear fixed-time filter is constructed, which not only obviates the complexity explosion issue but also enhances the convergence capability of interconnected power systems. Moreover, a dual dynamic parameter threshold Event-Triggered Mechanism (ETM) is developed. Influenced by multiple dynamic parameters, this mechanism achieves a more precise control of triggered conditions, drastically conserving the communication resources of the interconnected power systems and preventing the occurrence of Zeno behavior. Ultimately, the effectiveness of the proposed methods is demonstrated by the simulation results.