A two-loop optimization strategy for multi-objective optimal experimental design

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Abstract

A new strategy of optimal experimental design (OED) is proposed for a kinetically controlled synthesis system by considering both observation design and input design. The observation design that combines sampling scheduling and measurement set selection is treated as a single optimization problem arranged in the inner loop, while the optimization of input intensity is calculated in the outer loop. This multi-objective dynamic optimization problem is solved via the integration of particle swarm algorithm (for the outer loop) and the interior-point method (for the inner loop). Numerical studies demonstrate the efficiency of this optimization strategy and show the effectiveness of this integrated OED in reducing parameter estimation uncertainties. In addition, process optimization of the case study enzyme reaction system is investigated with the aim to obtain maximum production rate by taking into account of the experimental cost.
Original languageEnglish
Pages (from-to)803-808
Number of pages6
JournalIFAC-PapersOnLine
Volume49
Issue number7
Early online date1 Jun 2016
DOIs
Publication statusPublished - 9 Aug 2016
EventThe 11th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS-CAB 2016) - Trondheim, Trondheim, Norway
Duration: 6 Jun 20168 Jun 2016

Keywords

  • multi-objective optimal experimental design
  • process optimization
  • observation strategy
  • input design
  • parameter estimation
  • enzyme reaction system
  • kinetically controlled synthesis system

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