Adaptive Iterative Learning Boundary Control of a Flexible Manipulator with Guaranteed Transient Performance

This paper investigates the iterative learning control (ILC) problem of a flexible manipulator in the presence of external disturbances and output constraints. The dynamic behavior of the flexible manipulator is represented by partial differential equations (PDEs). We propose an ILC law to track the desired trajectory and suppress the vibration of the elastic deflection. The control scheme is based on a prescribed performance bound (PPB) which characterizes the maximum restrictions and convergence rate of the tracking error and deflection error. It is shown that the errors satisfy the prescribed performance bond all the time at any iterations. The established theoretical results are illustrated using numerical simulations for control performance verification.