An Iterative Learning Control Algorithm within Prescribed Input-Output Subspace

Abstract

In this paper, we consider an iterative learning control method (for short, ILC method). With the iteration of experiments, the ILC method yields the desired input for tracking the target trajectory. Most of former ILC methods use the time derivative of the error signal or the passivity of systems. Contrary to these former methods, this paper proposes an alternative ILC algorithm which does not use such things. This algorithm has the following property; the input space is restricted in the prescribed subspace, and the iterative learning law uses the modified error signal, which is projected on this input subspace. The effectiveness of the proposal method is demonstrated by a numerical example and an experiment.