Abstract The control strategies for batch processes in the past can be categorized into two levels. The higher level is economic optimization running at low frequency and the lower one tracks the given reference using MPC or PID at the higher level. The lower level regards all the disturbances as something to be rejected according to a quadratic based optimization objective. However, not all the disturbances are unfavorable to batch processes; some of them are helpful. In this paper, an economic batch-to-batch optimization method for batch processes is directly applied at the lower level. It replaces the former tracking strategy. With the information of disturbances collected from the previous batches, the iterative learning control strategy (ILC) can find out better operation profiles. ILC has the advantage of continuously improving the economic performance of the current batch with enriched information of disturbances from batch to batch. To demonstrate the potential applications of the proposed design method, a typical fed-batch bioreactor is applied.