A robust adaptive controller for rigid robots

Robust adaptive control schemes for robot manipulators are introduced. A new concept for the adaptive controller guarantees improved performance by gain dynamics relating to the small-gain adaptive mechanism. A control component in the driving acceleration input is exploited. It relates to Riccati equations. New gain dynamics and a linear feedback component increase the exponential convergence rate of a Lyapunov function. Unmodeled dynamics and bounded disturbances are considered in order to deal with the robustification issues. It is possible to adjust the region within which the tracking error is bounded by using design-parameters associated with a Riccati equation and the gain dynamics. This region is a ring-shaped area or a disk-shaped area in which the tracking errors and their derivatives remain. The suggested adaptive control is optimal in that it minimizes a performance index. Simulation results demonstrate the robustified property of the adaptive controller for rigid robots