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Integration of scheduling and control for batch processes using multi‐parametric model predictive control
Authors:Jinjun Zhuge  Marianthi G. Ierapetritou
Affiliation:Dept. of Chemical and Biochemical Engineering, Rutgers–The State University of New Jersey, Piscataway
Abstract:Integration of scheduling and control results in Mixed Integer Nonlinear Programming (MINLP) which is computationally expensive. The online implementation of integrated scheduling and control requires repetitively solving the resulting MINLP at each time interval. (Zhuge and Ierapetritou, Ind Eng Chem Res. 2012;51:8550–8565) To address the online computation burden, we incorporare multi‐parametric Model Predictive Control (mp‐MPC) in the integration of scheduling and control. The proposed methodology involves the development of an integrated model using continuous‐time event‐point formulation for the scheduling level and the derived constraints from explicit MPC for the control level. Results of case studies of batch processes prove that the proposed approach guarantees efficient computation and thus facilitates the online implementation. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3169–3183, 2014
Keywords:integration of scheduling and control  event‐point scheduling formulation  multi‐parametric Model Predictive Control  mixed integer nonlinear programming  batch processes
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