Stability of Discrete-time Iterative Learning Control with Random Data Dropouts and Delayed Controlled Signals in Networked Control Systems

This paper studies the robust stability of discrete-time iterative learning control (ILC) systems in a networked control system setting(NCS). First we consider the problem where data sent from a remote plant to the ILC algorithms is subject to random data dropouts. For this scenario we establish mean-square stability, taking into account the convergence of the covariance of the error along the iteration domain. Next, using this result, we derive a robust stability condition for a more general NCS-based ILC problem with data delays and dropouts in the control signals transmitted to the remote plant as well as data delays in output signals returned from the plant.