ADAPTIVE-CONTROL OF FLEXIBLE-JOINT ROBOTS

The problem of designing robust adaptive control strategies for a flexible-joint robot manipulator is considered. By utilizing the concept of integral manifolds, a corrected reduced-order model of the flexible system is first obtained. Adaptive control schemes for the corrected reduced-order model are then developed that otherwise would have been difficult to obtain for the full-order flexible system due to ill conditioning and curse of dimensionality. In this respect, the zeroth-order singular perturbation results that are applied to adaptive control of flexible-joint manipulators in the literature are generalized to include corrected adaptive control schemes. Two common adaptive control strategies are examined: 1) the adaptive inverse dynamics scheme and 2) the Slotine and Li scheme (although any other scheme can be treated similarly). The main contribution of this paper is to show how standard rigid adaptive control techniques may be generalized and improved on for successful application to a flexible-joint manipulator by developing corrected adaptive control laws. The outcome is a satisfyingly consistent and useful framework for dealing with such systems and one that opens the door to interesting generalizations of results previously restricted to rigid manipulators. The result is a robust adaptive control law that takes both parametric and dynamic uncertainties into account. Numerical simulations for a two-link flexible-joint manipulator are carried out to illustrate the potential and advantages of the new adaptive control schemes as compared to the above two standard techniques in the literature.