2D MODEL PREDICTIVE ITERATIVE LEARNING CONTROL SCHEMES FOR BATCH PROCESSES

Iterative learning control (ILC) system is modelled and treated as a 2D system in this paper. Based on single-batch and multi-batch cost functions, 2D model predictive iterative learning control (2D-MPILC) schemes are developed in the framework of model predictive control (MPC) for the 2D system. Structure analysis shows that the resulted 2D-MPILC laws are causal and they implicitly combine a time-wise MPC law with a cycle-wise ILC law to ensure the optimal control in 2D sense. To eliminate oscillating input, 2D control penalty is introduced to the 2D-MPILC design. The simulation results show that the proposed schemes are effective.