An Iterative Learning Control for a Class of Partially Feedback Linearizable Systems

Abstract

A class of single-input single-output nonlinear systems which are partially linearizable by state feedback is considered: feedback linearizable systems are included in such a class; no parametrization is required for the uncertainties which are required to satisfy the matching condition. Periodic reference signals with known period <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> are to be tracked by the output. Provided that known bounding functions on the uncertainties are available, a state feedback iterative learning control is designed which achieves asymptotic output tracking and guarantees bounded closed loop signals from any intial condition. The novel control tecnhique is illustrated for a single-link robot arm.