Recursive Composite Adaptation for Robot Manipulators

In this paper, we investigate the recursive implementation of composite adaptive control for robot manipulators. Via exploitation of the relation between the inertia matrix and the Coriolis and centrifugal matrix, we present the recursive algorithm for the derivation of the filtered manipulator model, which, to our knowledge, is the first result on this point in the literature. With this filtered model, the prediction error of the filtered torque is obtained and injected to the direct adaptation, forming the well-known composite adaptation law, with an acceptable amount of computation O(n2). A six degree-of-freedom (DOF) manipulator is employed as a simulation example to show the performance and the computational complexity of the proposed recursive algorithm.