Secure Control for T-S Fuzzy Wind Turbine Systems Under Hybrid Cyberattacks Via an Adaptive Memory Event-Triggered Mechanism

This paper addresses the secure control problem for the Takagi-Sugeno (T-S) fuzzy wind turbine system (WTS) subject to hybrid cyberattacks. To reduce system performance loss and redundant data transmission under such attacks, a novel adaptive memory event-triggered mechanism (ETM) is proposed, offering two key advantages. First, unlike traditional ETMs that rely solely on current system information, the adaptive memory ETM utilizes historical release data to adjust communication frequency and enhance control effectiveness. Second, an attack-related triggering condition and adaptive law are introduced to reduce the invalid data transmission induced by denial of service (DoS) attacks and extend the lifespan of the sensor node. Sufficient conditions are derived to ensure the mean-square $\mathcal {H}_{\infty }$ asymptotic stability of the resulting T-S fuzzy WTS, while also guaranteeing uniformly ultimate boundedness in the presence of DoS attacks. Finally, an illustrative example is used to show the effectiveness of the proposed method.