An investigation of nonlinear adaptive output feedback control for robotic manipulators

In this paper we present a nonlinear adaptive output feedback control algorithm. The algorithm is for model reference adaptive control of robotic manipulators. This algorithm uses model signals in the regressor and the linearization law and hence, does not require an observer. We show via various simulations that this algorithm has a region of convergence. We also show that the region of convergence can be increased if a normalizing factor is used in the adaptation law.