2-D theory based integrated predictive iterative learning control for batch process

An integrated predictive iterative learning control (IPILC) scheme for batch process is designed from a two-dimensional (2D) system point of view. The integrated control framework combines batch-wise ILC and time-wise model predictive control (MPC), referred as 2D-IPILC. In the trajectory tracking problem of batch process, the predictive model can be obtained based on the system response using 2D theory. The control profile in the current batch is updated by MPC, using a quadratic objective function defined over time horizon. The major advantages of the proposed design scheme are shown in the better tracking performance as well as faster convergence speed by taking into account the time-wise feedback control with-in the current batch. The simulation results demonstrate the effectiveness of the proposed scheme.