This paper presents a sliding-mode-based diagonal recurrent cerebellar model articulation controller (SDRCMAC) for multiple-input-multiple-output (MIMO) uncertain nonlinear systems. Sliding mode technology is used to reduce the dimension of the control system. Two learning stages are adopted to train the SDRCMAC and to improve the stability of the control system. Lyapunov stability theorem and Barbalat's lemma are adopted to guarantee the asymptotical stability of the system. Performance is illustrated on a two-link robotic control and motor control of the human arm in the sagittal plane.