Combined adaptive control of constrained robot manipulators

Abstract

Two reduced, unconstrained robot models, in which the constraints are satisfied automatically, are introduced. The force tracking error is dependent on both the position tracking error and the estimated parameter error, so that in the constrained adaptive robot manipulator control, the convergence of the estimated parameter error becomes more important than in the unconstrained adaptive robot control. However, in the direct adaptive controller, the parameter adaptation is only driven by the tracking error in the joint motion, while in indirect adaptive controller, the parameter estimation is only driven by the prediction error in the filtered joint torque. Based on this observation, a combined adaptive controller for constrained robot manipulators, with uncertain dynamic model parameters, is proposed. The combined adaptive control law, which is driven by both the tracking error and the prediction error, gives much improved stability properties for parameter estimation and force tracking.