Abstract
AbstractThis paper develops two proportional‐type (P‐type) networked iterative learning control (NILC) schemes for a class of discrete‐time nonlinear systems whose stochastic output packet dropouts are modeled as 0‐1 Bernoulli stochastic sequences. In constructing the NILC schemes, two kinds of compensation algorithm of the dropped outputs are given. One is to replace the instant‐wise dropped output data with the synchronous desired output data; the other is to substitute the dropped data with the consensus‐instant output data used at the previous iteration. By adopting the lifting technique, it is derived that under certain conditions the expectations of the tracking errors incurred by the proposed NILC schemes converge to zero along the iteration axis. Numerical experiments are carried out for validity and effectiveness.
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