Event-Triggered Mixed Non-Fragile and Measurement Quantization Filtering Design for Interval Type-2 Fuzzy Systems

This paper is concerned with the problem of event-triggered non-fragile H_∞ filter design for interval type-2 (IT2) fuzzy systems subject to output quantization. The nonlinear plant is efficiently described by an IT2 fuzzy model, and the lower and upper membership functions with weighting coefficients are employed to characterize parameter uncertainties in the plant. To enhance filter adaptability, an IT2 non-fragile fuzzy filter method is proposed to acquire available information for the unknown state of the plant, where the multiplicative gain variations is taken into account in the filter analysis design process. In order to avoid continuous communications and save limited bandwidth, a dynamic event-based mechanism is employed to adopt the limited communications links. Then, based on the Lyapunov theory together with the inequality technique, a filtering system with event-based mechanism and measurement quantization is analyzed and constructed. Moreover, the obtained sufficient conditions for system analysis are given in the form of linear matrix inequalities (LMIs). Finally, a numerical simulation is provided to verify the effectiveness of the proposed filter design strategy.

Abstract licence: CC BY-NC-ND

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