Dynamic real‐time optimization with closed‐loop prediction. Issue 9 (10th May 2017)

• Record Type: Journal Article
• Authors: Jamaludin, Mohammad Zamry; Swartz, Christopher L. E.
• Is Part Of: AIChE journal. Volume 63:Issue 9(2017)
• Page Start: 3896
• Page End: 3911
• Publication Date: 2017-05-10
• Subjects: dynamic real‐time optimization -- MPC -- economic optimization -- mathematical program with complementarity constraints -- KKT conditions; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; 660.28
• DOI: 10.1002/aic.15752
• Languages: English
• ISSNs: 0001-1541

Abstract

Abstract : Process plants are operating in an increasingly global and dynamic environment, motivating the development of dynamic real‐time optimization (DRTO) systems to account for transient behavior in the determination of economically optimal operating policies. This article considers optimization of closed‐loop response dynamics at the DRTO level in a two‐layer architecture, with constrained model predictive control (MPC) applied at the regulatory control level. A simultaneous solution approach is applied to the multilevel DRTO optimization problem, in which the convex MPC optimization subproblems are replaced by their necessary and sufficient Karush–Kuhn–Tucker optimality conditions, resulting in a single‐level mathematical program with complementarity constraints. The performance of the closed‐loop DRTO strategy is compared to that of the open‐loop prediction counterpart through a multi‐part case study that considers linear dynamic systems with different characteristics. The performance of the proposed strategy is further demonstrated through application to a nonlinear polymerization reactor grade transition problem. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3896–3911, 2017