An integrated predictive iterative learning control for batch process

In order to improve the convergence speed of iterative learning control (ILC), an integrated scheme for tracking problem of batch process is proposed by combining batch-to-batch P-type ILC and within-batch model predictive control (MPC). Based on a predefined batch-wise linear model of the process, the output of traditional P-type ILC can be predicted, and then MPC is induced to minimize a quadratic objective function within the current batch. The input is updated within the batch so that the output may approach the reference trajectory faster. An illustrative example is presented to demonstrate the performance of the proposed scheme.