Robust indirect-type iterative learning control design for batch processes with state delay, non-repetitive uncertainties and disturbances

A robust indirect-type iterative learning control scheme is developed for batch processes with state delays, time-varying uncertainties, and disturbances. In contrast to direct-type designs, the new scheme consists of two control loops, each of which can be designed independently. In the inner loop, a control law that is the sum of a generalised extended state observer-based state feedback and proportional plus integral control action acting on an error signal is designed for stability and robustness. The outer loop is designed to update the set-point command for the resulting closed-loop system. Finally, the stability theory for linear repetitive processes ensures robust tracking error convergence for the resulting dynamics in the presence of non-repetitive uncertainties and disturbances. Two numerical examples demonstrate the attributes of the new design.