Robust adaptive stabilization of flexible joint manipulators

A robust nonlinear adaptive control strategy is proposed to stabilize a robot manipulator subject to parametric and dynamic uncertainties. This is accomplished by utilizing state feedback and applying a control space transformation to a reduced-order model without parametric uncertainty. Under appropriate assumptions on the nature of the reduced-order uncertainties, an adaptive control strategy that compensates the nonlinear uncertainties is designed for the reduced-order feedback linearized system. An advantage of the proposed technique is that it requires external (feedback) linearization and update laws to be derived only from the reduced-order model, although the control strategy is applied to the full system. Numerical results for a single-link uncertain flexible-joint manipulator are included to illustrate the implementation and testing of the proposed method