Dynamic sum-based event-triggered H∞ filtering for networked T-S fuzzy wind turbine systems with deception attacks

This article is concerned with the dynamic sum-based event-triggered $H_{\infty }$ filtering issue for networked wind turbine systems subject to deception attacks and communication delays. By considering the time-varying wind power case rather than the existing maximum power case, a more general T-S fuzzy system with two premise variables is modeled for nonlinear wind turbine system. In order to save the communication cost, a novel dynamic sum-based event-triggered scheme is proposed, which has the following three merits. First, some past sampled measurements are utilized to reduce redundant transmissions. Second, an auxiliary dynamic variable based on the past sampled measurements is introduced in the triggering condition to further enlarge the triggering intervals. Third, a dynamic triggering threshold is designed, which can be regulated adaptively along with the system evolution. With the help of Lyapunov method and linear matrix inequality technique, some sufficient co-design conditions of $H_{\infty }$ filter and triggering matrices are derived for the T-S fuzzy filtering error system with deception attacks and communication delays. Lastly, some simulations are carried out to illustrate the advantages of the proposed strategy.