This paper aims to establish control theoretical validity of the feedback error learning scheme proposed as an architecture of brain motor control with deep physiological root in computational neuroscience. The feedback error learning method is formulated as a two-degree-of-freedom adaptive control. The stability of the adaptive control law is proved based on the strict positive realness, under the assumption that the plant is stable and stably invertible. Extension to non-invertible cases is also discussed. Some simulation results are given to illustrate the effectiveness of the method.