Iterative Learning Control Application to a 3D Crane System

This paper deals with the application of an Iterative Learning Control (ILC) structure to the position control of a 3D crane system in the crane position control problem. The control system structure involves Cascade Learning (CL) built around control a loop with a frequency domain designed lead-lag controller. The parameters of the continuous-time real PD learning rule as lead-lag controller are set such that to fulfil the convergence condition of the CL process. A set of real-time experimental results concerning a 3D crane system laboratory equipment is offered to validate the new CL-based ILC structure.

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