Iterative Optimal Control for Batch Process based on Generalized Predictive Control

A batch-to-batch iterative optimal control strategy general predictive control(GPC)-based for batch process-BGPC is proposed,which introduces the idea of batch-to-batch optimization into batch process.It uses model prediction errors from previous runs to improve current GPC model predictions based on the combination of GPC and iterative learning control(ILC).This algorithm can effectively overcome the model mismatch,unknown disturbance and parameter variation.The effectiveness and robustness of the proposed scheme are illustrated and verified on a numerical case and a simulated batch reactor system.