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.