Optimal design of sequential experiments for error-in-variables models

The optimal design of sequential experiments is well-established for explicit models, i.e. for models in which variables subject to error are expressed as functions of parameters and of independent variables measured accurately. Optimal design means therefore the determination of convenient values o...

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Bibliographic Details
Published inComputers & chemical engineering Vol. 17; no. 1; pp. 111 - 115
Main Authors Doví, V.G., Reverberi, A.P., Maga, L.
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 1993
Elsevier
Subjects
Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization
Applied sciences
Chemical engineering
Exact sciences and technology
Octane
Experimental design
Binary system
Toluene
Liquid vapor equilibrium
Theoretical study
Phase equilibrium
Modeling
Optimal design
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Summary:The optimal design of sequential experiments is well-established for explicit models, i.e. for models in which variables subject to error are expressed as functions of parameters and of independent variables measured accurately. Optimal design means therefore the determination of convenient values of the independent variables for the next experiment(s). In error-in-variables models there is no difference between independent and dependent variables and it is no longer possible to determine values of variables at which the experiment is to be carried out, but rather optimum nominal settings, from which the actual values of the experiment will differ due to the presence of experimental inaccuracy. In this paper optimum conditions for error-in-variables models are derived and an important special case is examined for comparison.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:0098-1354
1873-4375
DOI:10.1016/0098-1354(93)80008-B