Iterative Learning Control for Linear Systems with Fading Channels

This paper addresses the iterative learning control (ILC) for linear systems with random fading channels. The fading problem is a type of multiplicative uncertainties, which is generally caused by unreliable communication networks. It is modeled by a random variable with prior statistical information for correcting the received signals. Both output fading case and input fading case are discussed in this paper. The P-type learning algorithms with a constant learning gain are proposed with strict mean square boundedness convergence analysis. Illustrative simulations are provided to verify the theoretical results.