Abstract:

The problem of moving a rigid robot arm along a finite sequence of equilibrium points, with the last point coincident with the first one, is investigated. Such a sequence, referred to as a cycle, is to be repeated over and over in time, and a controller is sought which improves system performance by using positioning errors. Differently from learning control, no system initialization is required at the end of trial. After high gain feedback linearization of the robot dynamics, it is shown that linear, robust, finite dimensional algorithms can be set up to accomplish this task for unconstrained robots and robots subject to smooth bilateral constraints for which hybrid force control is of interest. An experiment on a two-link robot arm illustrates algorithm applicability.