Iterative Learning Control Strategy for Robotic Knee Exoskeleton in Rehabilitation

In this paper, we present a comprehensive study on the application of Iterative Learning Control (ILC) to knee exoskeletons, specifically designed for the rehabilitation of patients with walking disorders. The primary objective of our research is to analyze how ILC can enhance trajectory tracking in repetitive tasks such as assisted walking and precise knee positioning, which are crucial elements in the rehabilitation process.We demonstrate that ILC, by leveraging appropriately adjusted learning rates, ensures not only stable and precise control but also robust performance in the face of uncertainties and variations inherent in its clinical application. Our simulations reveal that ILC can overcome external disturbances while maintaining high performance, making it a promising solution for improving rehabilitation protocols.