An Estimator for Input Sent by ILC Controllers Through Multi-path Fading Channels

To ensure the convergence of objects controlled by the controller adopting iterative learning strategies through multi-path fading channels, this paper proposes an estimator for the controlled object to obtain the input sent by controllers. First, a controller adopting proportional learning strategies is considered, which shares input and output with the controlled object through the Rice fading channel. Secondly, utilizing the known information of both controllers and the Rice fading channel, the initial problem is converted into an estimation model. Finally, the estimator is created according to the orthogonality projection principle. Driving objects with the estimated input, significant improvements in tracking performance are achieved. Simulation results confirm the efficacy of the proposed estimator.