Event-Triggered H_∞ Filtering for Networked Takagi-Sugeno Fuzzy Systems Using Deviation Bounds of Normalized Membership Functions

摘要

This paper investigates event-triggered H_∞ filtering for networked Takagi-Sugeno systems with time-varying sampling periods. A new event-triggered transmission scheme (ETT scheme) is proposed to reduce network bandwidth utilization. Then, a synchronous fuzzy filter is introduced to estimate system real-time signals. Under the filtering framework with such a filter and the ETT scheme, the networked filtering error system is modeled as a threshold-error-dependent norm bounded uncertain fuzzy time-delay system with the deviations of normalized membership functions. By using the fuzzy Lyapunov-Krasovskii functional, a bounded real lemma is obtained such that the filtering error system is asymptotically stable with a prescribed H_∞ attenuation level. Then, two membership function deviation (MFD)-dependent conditions are presented to co-design the ETT scheme and the fuzzy filter. Finally, an illustrative example is given to show the effectiveness of the proposed MFD design approach.