On the parameterization of all admissible pairs in a class of CCF-ILC algorithms

This paper extends some recent results on the parameterization of all admissible pairs in a class of 2-parameter current-cycle-feedback ILC algorithms. In addition, a necessary and sufficient condition is given under which the associated set of equivalent controllers coincides with the set of all stabilizing controller

A class of non-contractive, trial-dependent update rules for Iterative Learning Control

In this paper, a family of trial-dependent update laws is studied and contrasted with a class of fixed update laws. In particular, it is investigated whether the principle of equivalent feedback extends to trial-dependent update laws. It turns out that this is not the case. Nonetheless, it is shown that a well-known performance bound arising in feedback control architectures, Bode's sensitivity integral, also applies her

On the use of noncausal LTI operators in iterative learning control

This paper demonstrates the use of noncausal operators in iterative learning control (ILC). First, it is shown that for a particular class of plants (having unstable zeros), perfect tracking can only be achieved by using noncausal operators. Then it is shown that with any converging algorithm (both causal and noncausal) we can associate a particular feedback controller. For causal algorithms this controller can be shown to be internally stabilizing. In the noncausal case, however, the associated controller is found to be generally destabilizing which implies that the existing notion of an equivalent controller for causal ILC does not extend to noncausal ILC