A feedback control framework for safe and economically‐optimal operation of nonlinear processes. Issue 7 (27th March 2016)

• Record Type: Journal Article
• Authors: Albalawi, Fahad; Alanqar, Anas; Durand, Helen; Christofides, Panagiotis D.
• Is Part Of: AIChE journal. Volume 62:Issue 7(2016)
• Page Start: 2391
• Page End: 2409
• Publication Date: 2016-03-27
• Subjects: economic model predictive control -- process safety -- process control -- process optimization; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; 660.28
• DOI: 10.1002/aic.15222
• Languages: English
• ISSNs: 0001-1541

Abstract

Abstract : Maintaining safe operation of chemical processes and meeting environmental constraints are issues of paramount importance in the area of process systems and control engineering, and are ideally achieved while maximizing economic profit. It has long been argued that process safety is fundamentally a process control problem, yet few research efforts have been directed toward integrating the rather disparate domains of process safety and process control. Economic model predictive control (EMPC) has attracted significant attention recently due to its ability to optimize process operation accounting directly for process economics considerations. However, there is very limited work on the problem of integrating safety considerations in EMPC to ensure simultaneous safe operation and maximization of process profit. Motivated by the above considerations, this work develops three EMPC schemes that adjust in real‐time the size of the safety sets in which the process state should reside to ensure safe process operation and feedback control of the process state while optimizing economics via time‐varying process operation. Recursive feasibility and closed‐loop stability are established for a sufficiently small EMPC sampling period. The proposed schemes, which effectively integrate feedback control, process economics, and safety considerations, are demonstrated with a chemical process example. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2391–2409, 2016