Feedforward control can significantly improve the performance of a system through compensation of disturbances. By exploiting measured data from previous tasks and a suitable feedforward parametrization, iterative feedforward control simultaneously attains high performance and good extrapolability of tasks. This paper aims to show that earlier contributions in this area suffer from a closed-loop identification problem. A novel solution is presented based on closed-loop identification techniques, which shows that existing feedforward control algorithms can be significantly enhanced. A simulation example confirms the existence of a closed-loop identification problem in earlier approaches and shows that the proposed solution is superior compared to pre-existing results.