Reliable measurement under sensor faults and disturbances/ noises is crucial for monitoring and control of electric motor drive systems operating under complex nonlinear dynamics and uncertainties. This work develops a new model-predictive fault estimation and accommodation scheme for the interval type–2 Takagi–Sugeno fuzzy models in discrete-time settings, remedying sensor faults and bounded disturbances within ellipsoids to enhance measurement reliability. A flexible and less conservative two-