ON TRAJECTORY TRACKING BY LEARNING OF FLEXIBLE-JOINT ARMS

This paper investigates, for two distinct classes of flexible joint ro bot arms, the problem of achieving exact output tracking over a finite time interval by means of a learning strategy. First, the problem of initial conditions compatibility with the trajectory to be tracked is discussed. Next, the author shows that after high-gain feedback linear ization, the control needed to track a family of link trajectories tha t satisfy some constraints on the initial conditions can be learned by means of a P-type algorithm.