Adaptive control of robots by linear time-varying dynamic position feedback

Abstract

A simple linear adaptive controller based on a reduced-order observer is proposed to treat the trajectory tracking control problem of robotic systems with unknown parameters and external disturbances. The novelty of our result lies in the fact that the controller is a linear time-varying dynamic position feedback compensator; the dimension of the observer, which is constructed only to estimate the velocity signal, is half the dimension of the robotic system and the attraction region of the closed-loop error system can not be only arbitrarily preassigned but also explicitly constructed. Moreover, as the adaptation is switched off, the boundedness of all the variables is still guaranteed and the trajectories of the closed-loop error system converge to any desired region. If the regressor matrix satisfies the persistent excitation condition, then our control algorithm also guarantees that the estimated values of the unknown parameters converge to the true ones.