A systematic design framework for iterative learning control with current feedback

Iterative learning control (ILC) has been a powerful control technique to improve systems' tracking performance over iterations. ILC with current feedback provides new opportunities for potential faster convergence. This paper proposes a systematic design framework for a generalized Nth-order ILC with current feedback information. The ILC design problem is formulated into an H-infinity optimal control design problem for a constructed system; the convergence over iterations and the stability of the feedback loop are guaranteed simultaneously. Numerical studies are performed to illustrate the design procedure and validate various types of ILCs designed under the proposed framework.