Event-triggered H_∞ filter design for sampled-data systems with quantization

This study verifies the H_∞ filter design for sampled-data systems with quantization and event-triggered schemes. Firstly, an event-triggered mechanism is presented to detect the release of the necessary sampled-data packet, which significantly reduces the limited network resources compared with the conventional time-triggered mechanism. Secondly, by considering the impact of quantization on the sampled-data system and using the time interval analysis approach, a new sampled-data filtering error model is presented. Then, the Lyapunov-Krasovskii functional (LKF) approach is utilized to derive the required conditions to ensure the asymptotical stability and attain the prescribed H_∞ performance for the mentioned system by solving a group of linear matrix inequality (LMIs). Consequently, the corresponding event-triggered and H_∞ parameters are co-designed. Finally, the efficiency and the advantage of the presented approach are demonstrated via a mass-spring system example.