Adaptive control of flexible joint robots

The problem of designing a robust adaptive control strategy for flexible joint robot manipulators is considered. By utilising the concept of integral manifolds, reduced-order models of the flexible system are obtained. This makes it possible to develop adaptive control schemes for the flexible full-order system at the reduced-order level, which otherwise would be difficult due to ill-conditioning and the curse of dimensionality. Two common adaptive control strategies are examined: (i) the adaptive inverse dynamics and (ii) the Slotine and Li algorithm. It is shown how these standard rigid adaptive control techniques can be generalized and improved for successful application to flexible joint manipulators. The result is robust adaptive control laws which take both parametric and dynamic uncertainties into account. Numerical simulations for a two-link flexible joint manipulator illustrate the potential and advantages of the new adaptive schemes as compare to the two standard algorithms in the literature