ITERATIVE LEARNING CONTROL WITH ADVANCED OUTPUT DATA

In this paper, iterative learning control using output data, which are more advanced than the relative degree of the system, is being investigated. It is known that the output error can be made zero with the conventional iterative learning control in which the input is updated with the output data advanced by the relative degree. However, the input can become too large for nonminimum phase systems. With the proposed scheme, the input can be prevented from becoming unnecessarily too large, which in turn makes it practical to apply iterative learning control for nonminimum phase systems. Simulations are performed to show the effectiveness of the scheme