화학공학소재연구정보센터
Journal of Process Control, Vol.81, 172-189, 2019
A two-dimensional design of model predictive control for batch processes with two-dimensional (2D) dynamics using extended non-minimal state space structure
A modified two-dimensional (2D) structure based control strategy that incorporates model predictive control (MPC) and iterative learning control (ILC) in 2D sense is developed for batch processes in this article. To enhance the control effect of the conventional 2D model predictive iterative learning control (2D-MPILC), an improved non-minimal form of state space model is utilized in the developed method. Through employing such model, the dynamics of the closed-loop system can be regulated by tuning extra process variables. In other words, additional degrees of freedom are achieved in the novel controller design, and the modified control performance is expected for the proposed algorithm. The simulation results on two processes evaluate the effectiveness of the presented 2D-MPILC strategy finally. (C) 2019 Elsevier Ltd. All rights reserved.