This study focuses on biomimetic sensory motor control of a robotic arm. We have developed a command circuit that was mathematically deduced from physical and mathematical constraints describing the function of cerebellar pathways. The control circuit contains an internal predictive model of the direct biomechanical function of the limb placed in a closed loop, so that the circuit computes an approximate inverse function. The structure of the model resembles the anatomic connectivity of the cerebellar pathways. In this paper, we present an application of this model to the control of a 2-link robotic arm actuated by four single-joint McKibben muscles and report the results obtained by simulation and real-time learning of 2 degrees of freedom pointing movements.