Adaptive inertia compensation using a cerebellar model algorithm

A method for adaptively compensating for inertia in the control of robotic manipulators is described. The method uses an adaptive network which can be related to a number of contemporary models of the cerebellum. Simulations of a three-link planar manipulator show that the algorithm compensates for inertia during a movement without a priori knowledge. The fact that motions need not be repetitive gives the algorithm significant practical value