Resilient Event‐Triggered Control of Interval Type‐2 Fuzzy Systems via Functional Observers

Abstract

This article addresses the resilient output‐feedback control problem for discrete‐time interval type‐2 (IT2) Takagi–Sugeno (TS) fuzzy systems operating under imperfect measurement and modeling uncertainties. First, an adaptive saturation mechanism driven by an a priori predicted output is introduced to construct a saturation‐protected measurement signal and avoid algebraic‐loop issues in real‐time implementation. Then, an admissible unknown‐input functional observer is developed to estimate the required augmented‐state function, and a rank‐condition‐based criterion is established for the solvability of the observer matching equations. Next, a dynamic event‐triggered fuzzy controller is designed using the estimated functional variable, which compensates for the unknown‐input‐related component while reducing unnecessary signal transmissions. Finally, by constructing a descriptor closed‐loop representation that incorporates the plant dynamics, observer error, transmission error, saturation residual, and MF mismatch, sufficient linear matrix inequality (LMI) conditions are derived to guarantee asymptotic stability and mixed performance. The proposed framework offers an implementable solution for resilient unknown‐input functional‐observer (UIFO) based event‐triggered control of IT2 fuzzy systems.