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Hierarchical optimal control of a binary distillation column
Author(s) -
Ramezani Mohammad Hossein,
Sadati Nasser
Publication year - 2018
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2473
Subject(s) - tray , fractionating column , distillation , controller (irrigation) , binary number , column (typography) , reliability (semiconductor) , control theory (sociology) , mathematical optimization , function (biology) , computer science , optimal control , control (management) , mathematics , engineering , chemistry , chromatography , artificial intelligence , arithmetic , biology , telecommunications , power (physics) , quantum mechanics , evolutionary biology , agronomy , mechanical engineering , physics , frame (networking)
Summary This paper presents a two‐level optimal control for the binary distillation column. From the control point of view, the binary distillation column is a high‐order system consisting of several interconnected subsystems (trays) that aim to maximize output purity. Controlling the system in a hierarchical manner not only decreases complexity and solution time but also can improve the control structure's reliability. In this study, the distillation column is decomposed into N T second‐order subsystems, each representing one stage (one tray). Accordingly, the cost function is decomposed, and thus, the overall problem is converted into N T lower‐order subproblems where each tray has its own controller. A two‐level interaction prediction approach provides optimal control for the overall system. The task of the first level is to solve the subproblems using the predicted values of the coordination parameters, whereas the second level acts as a coordinator to update the coordination parameters. Simulation results show the capability and efficacy of the proposed two‐level control method in finding the optimal solution with less complexity and lower solution time than those of the centralized method.

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