Abstract: A cooperative design method integrating a learning observer and fault-tolerant control based on the Interval Type-2 Takagi-Sugeno (IT2 T-S) fuzzy model is proposed for nonlinear systems subject to uncertainties, external disturbances, and actuator faults. First, mismatched membership functions are employed to construct the system model, with parameter uncertainties characterized by the upper and lower bounds of the fuzzy intervals. Second, an IT2 T-S fuzzy learning observer is designed to simultaneously estimate the system states and actuator faults in real time, significantly suppressing the effects of uncertainty and external disturbances. Then, based on the fault estimation information, a fault-tolerant controller with membership-dependent H_\infty performance is constructed, ensuring both finite-time stability of the closed-loop system and the achievement of a prescribed H_\infty performance index. Finally, existence conditions for the observer and controller are derived using Lyapunov theory and transformed into linear matrix inequalities (LMIs) to solve for the gain matrices. To validate the performance of the proposed method, comprehensive numerical simulations are conducted on two types of nonlinear systems: a mass-spring-damper system and an inverted pendulum. The results consistently demonstrate that the proposed method not only achieves accurate estimation and rapid adaptive compensation of system dynamics and fault signals but also fundamentally guarantees the stability and convergence of the closed-loop system within a finite time.