Optimal experimental design for an enzymatic biodiesel production system

Hui Yu; Hong Yue; Peter Halling

doi:10.1016/j.ifacol.2015.09.141

Optimal experimental design for an enzymatic biodiesel production system

Hui Yu, Hong Yue, Peter Halling

Research output: Contribution to conference › Proceeding › peer-review

9 Citations (Scopus)

145 Downloads (Pure)

Abstract

Two optimal experimental design (OED) problems for an enzymatic biodiesel production system are investigated to improve parameter estimation quality. An orthogonalized sensitivity analysis method is firstly implemented to select important parameters. Next the design of measurement set and sampling strategy is developed in the form of two convex optimization problems which are solved by the interior-point algorithm and the Powell’s method, respectively. Simulation results demonstrate the function of OED in reducing parameter estimation errors. The biodiesel concentration is identified to be the most valuable state variable observation, and the parameter estimation accuracy can be improved through optimal sampling design.

Original language	English
Pages	1259 – 1264
Number of pages	6
DOIs	https://doi.org/10.1016/j.ifacol.2015.09.141
Publication status	Published - 7 Jun 2015
Event	9th IFAC Symposium on Advanced Control of Chemical Processes - ADCHEM 2015 - Whistler, British Columbia, Canada Duration: 7 Jun 2015 → 10 Jun 2015

Conference

Conference	9th IFAC Symposium on Advanced Control of Chemical Processes - ADCHEM 2015
Country	Canada
City	Whistler, British Columbia
Period	7/06/15 → 10/06/15

Keywords

optimal experimental design (OED)
enzymatic biodiesel reaction system
measurement set selection
optimal sampling strategy
parameter estimation
local sensitivity analysis (LSA)

Access to Document

10.1016/j.ifacol.2015.09.141

Yu-etal-ADCHEM2015-optimal-experimental-design-enzymatic-biodiesel-production-systemAccepted author manuscript, 401 KB

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Peter Halling
- p.j.halling@strath.ac.uk
- Pure And Applied Chemistry - Visiting Professor
Person: Visiting Professor

Cite this

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title = "Optimal experimental design for an enzymatic biodiesel production system",

abstract = "Two optimal experimental design (OED) problems for an enzymatic biodiesel production system are investigated to improve parameter estimation quality. An orthogonalized sensitivity analysis method is firstly implemented to select important parameters. Next the design of measurement set and sampling strategy is developed in the form of two convex optimization problems which are solved by the interior-point algorithm and the Powell{\textquoteright}s method, respectively. Simulation results demonstrate the function of OED in reducing parameter estimation errors. The biodiesel concentration is identified to be the most valuable state variable observation, and the parameter estimation accuracy can be improved through optimal sampling design.",

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doi = "10.1016/j.ifacol.2015.09.141",

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AU - Yu, Hui

AU - Yue, Hong

AU - Halling, Peter

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N2 - Two optimal experimental design (OED) problems for an enzymatic biodiesel production system are investigated to improve parameter estimation quality. An orthogonalized sensitivity analysis method is firstly implemented to select important parameters. Next the design of measurement set and sampling strategy is developed in the form of two convex optimization problems which are solved by the interior-point algorithm and the Powell’s method, respectively. Simulation results demonstrate the function of OED in reducing parameter estimation errors. The biodiesel concentration is identified to be the most valuable state variable observation, and the parameter estimation accuracy can be improved through optimal sampling design.

AB - Two optimal experimental design (OED) problems for an enzymatic biodiesel production system are investigated to improve parameter estimation quality. An orthogonalized sensitivity analysis method is firstly implemented to select important parameters. Next the design of measurement set and sampling strategy is developed in the form of two convex optimization problems which are solved by the interior-point algorithm and the Powell’s method, respectively. Simulation results demonstrate the function of OED in reducing parameter estimation errors. The biodiesel concentration is identified to be the most valuable state variable observation, and the parameter estimation accuracy can be improved through optimal sampling design.

KW - optimal experimental design (OED)

KW - enzymatic biodiesel reaction system

KW - measurement set selection

KW - optimal sampling strategy

KW - parameter estimation

KW - local sensitivity analysis (LSA)

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