<p>This paper presents a robust output feedback control framework for nonlinear systems represented by polynomial fuzzy models, incorporating a dynamic event-triggering mechanism to improve resource efficiency. Unlike conventional sampled-data controllers, the proposed strategy adjusts the transmission of output measurements online according to the system’s real-time behavior, by increasing component life spans and reducing energy consumption. A key feature of this work is the explicit inclusion of an energy-bounded disturbance term in the model formulation, which enables the controller to preserve stability and performance in the presence of external perturbations and modeling uncertainties. Asymptotic stability of the closed-loop system is established using a Lyapunov–Krasovskii functional, and the resulting conditions are derived in a sum-of-squares (SOS) framework, leading to a tractable controller synthesis procedure. Numerical simulations illustrate that the proposed method achieves robust stabilization with significantly fewer control transmissions compared with a static event-triggered strategy.</p>