Iterative learning control with dirac-delta function under state alignment condition

In this paper, we develop iterative learning control (ILC) algorithms when the final states of previous iteration are equal to the initial states of current iteration, which is called state alignment. When a new iteration begins along continuous time domain without stopping for a reset, the typical ILC algorithm is modified using dirac-delta function such that the state alignment condition is satisfied.