A robust pinch detection algorithm which can be implemented in a cheap microprocessor is proposed for safety power window systems. To deal with the problems caused by performance degradation of a Hall sensor or real driving situations, the proposed algorithm makes use of the H∞, state estimation technique. The motivation of this approach comes from the advantage that the H∞ filter can minimize or bound the worst-case estimation error energy for all bounded energy disturbances. Herein, the pinch torque rate estimator is derived by applying the steady-state H ∞ filter to the augmented model which includes the motor dynamics and an additional torque rate state. Then, by redesigning the estimator to be appropriate for real-time implementation, the torque rate estimate can be calculated more simply than the previous method . Experimental results verify that, with a small amount of computation, the proposed pinch detection algorithm provides fast pinch detection performance similar to the existing method. Furthermore, it guarantees robustness against the worst-case measurement noises.