Title: Computation of optimal identification experiments for nonlinear dynamic process models: a stochastic global optimization approach
Authors: Banga, JR ×
Versyck, KJ
Van Impe, Jan #
Issue Date: 2002
Series Title: Industrial & engineering chemistry research vol:41 issue:10 pages:2425-2430
Conference: date:CSIC, Proc Engn Grp, Inst Invest Marinas, Vigo 36208, Spain; Janssen Pharmaceut, Chem Prod Engn, B-2440 Geel, Belgium; Katholieke Univ Leuven, Dept Chem Engn, BioTeC, B-3001 Heverlee, Belgium
Abstract: The problem of optimal experimental design (OED) for parameter estimation of nonlinear dynamic systems is considered. It is shown how this problem can be formulated as a dynamic optimization (optimal control) problem where the performance index is usually a scalar function of the Fisher information matrix. Numerical solutions can be obtained using direct methods, which transform the original problem into a nonlinear programming (NLP) problem via parametrizations. However, because of the frequent nonsmoothness of the cost functions, the use of gradient-based methods to solve this NLP might lead to local solutions. Stochastic methods of global optimization are suggested as robust alternatives. A case study considering the OED for parameter estimation in a fed-batch bioreactor is used to illustrate the performance and advantages of two selected stochastic algorithms.
ISSN: 0888-5885
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Bio- & Chemical Systems Technology, Reactor Engineering and Safety Section
× corresponding author
# (joint) last author

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