Predictive time-sequence iterative learning control with application to a fermentation process

A predictive time-sequence iterative learning control method is proposed in this paper and its potential application to some industrial processes that are difficult to describe mathematically but often with input/output data measured from the processes available, such as fed-batch fermentation processes, has been studied. By the proposed method, the control performance can be improved in the first trial instead of waiting until the following trials. The idea of the proposed method is to use predictive learning for the future control in the same batch operation, and to use penalty/reward to achieve improvement on past control experiences. A simulation study in applying the proposed learning control method to a fed-batch fermentation process is illustrated