Optimal filters for the input conveyed by controllers using iterative learning strategies with alternating data losses and fading

Abstract The time‐varying nature of wireless channels leads to alternating data losses and fading, which pose significant challenges for ensuring the tracking accuracy of remotely controlled objects using iterative learning strategies. To address this challenge, we developed a filter to estimate the input conveyed by controllers through the time‐varying channel. First, a transmission model is formulated to depict the combined effects of alternating data losses and fading. Second, the formulated model is integrated with the given control strategy to form a filtering model. Third, the filter based on projection theory is proposed. Finally, numerical results validate that feeding objects with the filtered input can significant improve the tracking accuracy.