Experimental study on pseudo-downsampled ILC with time shift along iteration axis

Abstract

A pseudo-downsampled iterative learning control (ILC) scheme with a time shift along iteration axis is proposed. In this scheme, there are two sampling rates: a system with a fast sampling rate and an ILC scheme with a downsampled slow sampling rate. After one cycle, the input update points of ILC are shifted one sampling period w.r.t. fast system sampling rate. That is, there is always a time shift for ILC input updates points along iteration axis for two successive cycles. This process is repeated so that the input on every point w.r.t. fast system sampling rate can be updated once every several cycles. Theoretical basis and the design of the proposed ILC are given. The advantages include that it can guarantee the good learning transient; it can track high frequency trajectory; it needs not a filter design; and it can deal with initial position offset. Experimental results are presented to verify the proposed scheme