This chapter considers a very different application from that introduced in the previous two chapters. We discuss the application of iterative learning control to robot-assisted upper limb stroke rehabilitation. We develop a combined feedback and iterative learning control-based scheme for regulating the assistive electrical stimulation applied such that the patient gradually recovers lost functionality by repeated attempts at a finite duration task. Convergence performance of Norm Optimal Iterative Learning Control and its acceleration using error corrected reference, as well as the effect of feedback controller, are illustrated via numerical simulations.