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An economic objective for the optimal experiment design of nonlinear dynamic processes. (English) Zbl 1309.93156

Summary: State-of-the-art formulations of optimal experiment design problems are typically based on a design criterion which allows us to optimize a scalar map of the predicted variance-covariance matrix of the parameter estimate. Famous examples for such scalar objectives are the A-criterion, the E-criterion, or the D-criterion, which aim at minimizing the trace, maximum eigenvalue, or determinant of the variance-covariance matrix. In this paper, we propose a different way of deriving an economic design criterion for the optimal experiment design. Here, the corresponding analysis is based on the assumption that our ultimate goal is to solve an optimization problem with a given economic objective that depends on uncertain parameters, which have to be estimated by the experiment. We illustrate the approach by studying a fedbatch bioreactor.

MSC:

93E10 Estimation and detection in stochastic control theory
93B60 Eigenvalue problems
93C10 Nonlinear systems in control theory
92C40 Biochemistry, molecular biology

Software:

ACADO
PDFBibTeX XMLCite
Full Text: DOI

References:

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