RECURSIVE IDENTIFICATION OF PHYSICAL PARAMETERS IN A FLEXIBLE ROBOT ARM

Abstract

ABSTRACT Recursive identification of a physically parameterized model of a single link flexible robot arm is considered. The parameters are estimated using a recursive prediction error method applied to a linear continuous time model structure and discrete time data. The algorithm is applied to real data from an industrial robot, and three important parameters are identified using only measurements of the motor angle. The experiments show that the particular parameter that is estimated will have big influence on the algorithm behavior.