Event-based H∞ filtering for sampled-data systems

This paper is concerned with event-based H ∞ filtering for sampled-data systems. First, an event-based data packet processor is introduced to release sampled measurement outputs only if an event condition is violated. As a result, communication resources can be saved significantly while preserving the desired H ∞ performance. Second, the resulting filtering error system is modeled as a system with an interval time-varying delay. By employing the Lyapunov-Krasovskii functional approach, a new bounded real lemma (BRL) is established such that the filtering error system is asymptotically stable with the prescribed H ∞ performance. Third, by performing an invertible linear transformation on the filtering error system, a linear matrix inequality (LMI)-based sufficient condition, which is equivalent to the condition in the BRL, is obtained on the feasibility of the event-based H ∞ filtering problem. Consequently, suitable H ∞ filters and the event parameters in the event condition can be co-designed provided that a set of LMIs are satisfied. Finally, a mechanical system with two masses and two springs is given to show the effectiveness of the proposed method.