Conditional iterative learning control for non-linear systems with non-parametric uncertainties under alignment condition

Abstract

A conditional iterative learning control (ILC) is derived for uncertain non-linear systems to track repetitive trajectory under the alignment initial condition. The learning of the conditional ILC is performed, only if the tracking error is dominated by the input instead of the initial conditions. The major advantage of this method is that it can simultaneously handle non-parametric uncertainties and the alignment initial condition. A simulation example is presented to illustrate the performance and implementation of the conditional ILC.