Generalized predictive control with iterative learning for batch repeatable processes

In this paper, a generalized predictive control with iterative learning (ILGPC) was proposed for a batch repeatable process. An iterative learning feed-forward loop was added in GPC loop by utilizing the previous process I/O information. The predictive estimation and learning of the partial repeatable disturbance improved the control performance of repeatable operation process and reduced the tracking error. The stability of the algorithm is also analyzed, and furthermore the stability and the robustness of the proposed algorithm are demonstrated by the simulation results of a batch polymerization reactor.