  The ability to manipulate clouds of ultra-cold atoms is crucial for modern
experiments on quantum manybody systems and quantum thermodynamics as well as
future metrological applications of Bose-Einstein condensate. While optical
manipulation offers almost arbitrary flexibility, the precise control of the
resulting dipole potentials and the mitigation of unwanted disturbances is
quite involved and only heuristic algorithms with rather slow convergence rates
are available up to now. This paper thus suggests the application of iterative
learning control (ILC) methods to generate fine-tuned effective potentials in
the presence of uncertainties and external disturbances. Therefore, the given
problem is reformulated to obtain a one-dimensional tracking problem by using a
quasicontinuous input mapping which can be treated by established ILC methods.
Finally, the performance of the proposed concept is illustrated in a simulation
scenario.
