This study presents a novel fuzzy observer synthesis method for a class of nonlinear systems characterized by discrete-time interval type-2 Takagi–Sugeno fuzzy models, which involves measurable/unmeasurable premise variables and bounded disturbances within ellipsoids. A nonfragile observer design strategy is employed to ensure resilience against potentially stochastic variations in the observer gain. A simplified adaptive event-triggered communication mechanism with a threshold that can be dynamically adjusted online is proposed to mitigate the network transmission pressure and reduce the energy consumption. A new definition of the stochastic quadratic boundedness employing multiple Lyapunov functions is proposed to concurrently determine the observer and event generator parameters. Resorting to this definition guarantees the stochastically quadratic boundedness and the stability of the estimation error systems. The codesign of the desired observer and event generator parameters is accomplished using slack-variable and convex optimization techniques. Further, the corresponding upper bounds on the estimation errors are explicitly provided. The feasibility and the superiority of the proposed method are validated through a continuously stirred tank reactor system and a tunnel diode circuit model.