Adaptive Iterative Learning Control of Disk‐Beam‐Mass System With Input Saturation

This paper focuses on the vibration suppression of a rotating disk‐beam‐mass system subject to input saturation. The system consists of a one‐dimensional flexible beam affixed to a rotating rigid disk at one end and a payload mass at the opposite boundary. We posit that the system experiences unknown spatiotemporal distributed disturbances and time‐varying boundary disturbances. To suppress the vibrations, an adaptive boundary iterative learning control law is designed. It integrates historical iteration data with real‐time boundary state feedback to handle actuator saturation. Concurrently, an iteration‐domain adaptive learning mechanism is constructed to compensate for parameter uncertainties and external disturbances. Applying the Lyapunov theory, we demonstrate that all signals in the closed‐loop system remain uniformly bounded in each iteration. Furthermore, the beam's transverse displacement asymptotically converges to zero along the iteration axis. Finally, we conduct numerical simulations to validate the applicability and efficacy of the proposed adaptive boundary controller.