Predictive iterative learning control based on averaging technology for networked systems with fading channels and data loss

This paper proposes a unique general averaging (GA)-based predictive iterative learning control (PILC) method for networked systems with both data loss and fading channels. The objective is to eliminate the adverse effects of data loss and fading channels via prediction error. First, an averaging technique using all historical information is introduced into the prediction model and controller, and the control input is updated only when the data is successfully transmitted. Then, the convergence of the mean tracking error along the iterative domain of the GA-based PILC is obtained using a composite energy function method in a stochastic framework. Finally, the effectiveness of the proposed GA-based PILC method is validated through theoretical analysis and two simulation examples.