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Model-Based Experimental Design: A Comparison between Sequential and Simultaneous Optimization approaches

Hoang, DM, Merchan, VA, Barz, T, Biegler, L, Arellano-Garcia, H and Wozny, G (2013) Model-Based Experimental Design: A Comparison between Sequential and Simultaneous Optimization approaches In: WCCE9: 9th World Congress of Chemical Engineering, 2013-08-18 - 2013-08-23, Seoul, South Korea.

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Mathematical models are essential for chemical processes since they contribute to both identification and manipulation of process mechanisms, e.g. in reaction systems, separation processes and process controls. The methodologies of model-based experiment design aim at reducing the uncertainties of estimated model parameters, and thus, make the identification and use of these models possible. Up to now, sequential optimization approaches have been applied to solve the related extended optimal control problem. In this contribution, a substantial comparison between the sequential and the simultaneous optimization approach for optimal model-based experimental design is presented with respect to convergence behavior and computational load. Moreover, both approaches are compared regarding high order and continuous control trajectories as well as restrictions from the process. Process restrictions, especially regarding state variables and continuity of control trajectories have a tremendous importance with respect to the practical implementation, but are mostly just touched or totally neglected during the optimization steps so far. The results are discussed by the application on a CSTR example.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Chemical and Process Engineering
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
Hoang, DM
Merchan, VA
Barz, T
Biegler, L
Arellano-Garcia, H
Wozny, G
Date : 18 August 2013
Depositing User : Symplectic Elements
Date Deposited : 20 Feb 2017 16:20
Last Modified : 31 Oct 2017 19:08

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