Integrated tracking control strategy for batch processes using a batch-wise linear time-varying perturbation model

An integrated batch-to-batch control and within-batch online control strategy for tracking product quality trajectories in batch processes is proposed. On the basis of a batch-wise linear time-varying perturbation model, iterative learning control (ILC) is implemented for batch-to-batch control and the convergence of tracking errors under ILC is guaranteed. Within a batch, a predictive model is constructed by directly partitioning the linear time-varying model according to time, then batch model predictive control with shrinking horizons is applied online to reduce the effects of model-plant mismatch and/or unknown disturbances. By properly combining these two control methods, the integrated control strategy can complement both methods to obtain good performance. The proposed strategy is demonstrated on a simulated batch polymerisation process, and the results show that the performance can be improved quite significantly under the integrated control strategy than only under ILC, especially when disturbances occur.