Padé approximants in linear repetitive learning controls for robotic manipulators

Abstract

We present the use of [m, m]-Padé approximants in the implementation of repetitive learning controls for the asymptotic link position tracking in robotic manipulators with uncertain dynamics and periodic position reference signals (with known period). The resulting linear learning controllers are described by transfer functions exhibiting all their poles with negative real part. Analyses from both theoretical and experimental points of view are carried out.