Iterative Learning Control Design without a Priori Knowledge of Control Directions

Abstract

In this work we explore the possibility of designing a suitable iterative learning control system without a priori knowledge of the control directions. By incorporating a Nussbaum-type function, a new learning control mechanism is constructed with both differential and difference updating laws. The new learning control mechanism can warrant a L2-norm convergence of the tracking error sequence in the iteration domain. The new learning control can be applied to systems without the identical initial resetting condition (i.i.c.), and in the presence of time varying parametric uncertainties associated with non-global Lipschitz nonlinearities.