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Related Experiment Video

Updated: Feb 6, 2026

Feeding Experimentation Device FED: Construction and Validation of an Open-source Device for Measuring Food Intake in Rodents

Feeding Experimentation Device FED: Construction and Validation of an Open-source Device for Measuring Food Intake in Rodents

Published on: February 21, 2017

Successive complementary model-based experimental designs for parameter estimation of fed-batch bioreactors.

Jung Hun Kim¹, Jong Min Lee²

¹School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea.

Bioprocess and Biosystems Engineering

|August 13, 2018

Summary

This study introduces an anticorrelation parameter estimation scheme for dynamic bioreactor models. It minimizes parameter correlation by sequentially designing experiments to maximize information gain from each batch.

Keywords:

Bioreactor Model-based design of experiment Parameter correlation Parameter estimation Sequential design of experiment

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Area of Science:

Biotechnology
Chemical Engineering
Process Systems Engineering

Background:

Dynamic models for fed-batch bioreactors often exhibit high parameter correlations.
High parameter correlation hinders obtaining reliable parameter estimates.

Purpose of the Study:

To propose an anticorrelation parameter estimation scheme for fed-batch bioreactors.
To improve the reliability of parameter estimates in dynamic bioreactor models.

Main Methods:

Iterative parameter estimation and model-based design of experiment (MBDOE).
MBDOE objective defined by a priori system analysis for sequential batch processing.
Scheme illustrated on a fed-batch bioreactor model.

Main Results:

The proposed scheme effectively reduces parameter correlation.
Sequential batch experiments supplement information gaps from previous batches.
Reliable parameter estimates are achieved through reduced correlation.

Conclusions:

The anticorrelation parameter estimation scheme enhances model reliability for bioreactors.
MBDOE tailored to system analysis is crucial for efficient sequential experimentation.
This approach is vital for accurate dynamic modeling in bioprocesses.