Adaptive Predictive Control by Open-Loop- Feedback-Optimal Controller for Cultivation Processes

  • Process description, optimization and control using mathematical models are an innovative and efficient approach in the process development. And the development of mathematical models is also time and cost consuming.The use of a highly adaptive general model for bio-processes can reduce the time for modeldevelopment. Because it takes only the adjustment of model parameters to achieve the adaptation of a process model to a new organism or product. Development of a general process model with high adaptability was one of the main goals of "ProTool". A general process model is not bound to a certain cell line and microorganism, but adapts itself to a variety of organisms and different scenarios. This process model will be used for data interpretation, process monitoring, recipe optimization and the verification of control concepts as well as the basis of a virtual bioreactor. Correspondingly, the development of an advanced controller to achieve an optimized process control adapting the general model (named as the open-loop-feedback-optimal(OLFO) controller) was another main goal of "ProTool", which is also the core task of my dissertation. A structured model consisting of four biomass compartments is working as the general model which is able to describe the cultivation of different organisms. Based on this model, online parameter identification is carried out periodically with the actual process data collected from the plant and laboratory analysis. And the new estimated process parameters and the updated process state variables are used in calculating an optimal control profile. The model parameters are updated at desired period using the extended database to reduce the plant model mismatch to improve the performance of the optimizer. This work outlines the advantages to apply the OLFO controller in fermentation processes. The results obtained in both simulation and real processes show the efficiency of the OLFO controller for online fermentation process control.

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Publishing Institution:IRC-Library, Information Resource Center der Jacobs University Bremen
Granting Institution:Jacobs Univ.
Author:Meijie Li
Referee:Mathias Winterhalter, Volker C. Hass, Roland Benz, Florian Kuhnen
Advisor:Mathias Winterhalter
Persistent Identifier (URN):urn:nbn:de:gbv:579-opus-1005963
Document Type:PhD Thesis
Date of Successful Oral Defense:2015/10/16
Date of First Publication:2016/08/15
Academic Department:Life Sciences & Chemistry
PhD Degree:Biochemical Engineering
Focus Area:Health
Other Organisations Involved:Hochschule Bremen
Library of Congress Classification:T Technology / TP Chemical technology / TP248.13-248.65 Biotechnology / TP248.24-248.25 Processes, operations, and techniques / TP248.25.M39 Mathematical models
Call No:Thesis 2015/56

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