An intermittent iterative learning control design based on a 2D roesser system

In network-based iterative learning control (ILC) systems, intermittent measurement often occurs during the data packet transfers from the remote plant to the ILC controller. In this paper, measurement missing is modeled by stochastic variables satisfying the Bernoulli random binary distribution, and then the design of ILC law is transformed into a feedback control problem of a 2D stochastic system described by Roesser model. A sufficient condition for mean-square asymptotic stability is established by means of linear matrix inequality (LMI) technique, and formulas can be given for the control law design simultaneously. A numerical example illustrates the effectiveness of the proposed results.