Sensorless Nonlinear Control of Fed-Batch \(Escherichia\,coli\) Cultivation Bioprocess Using the State-Dependent Approach

The cultivation of Escherichia coli bacteria is widely used by geneticists and biopharmaceuticals to produce medicines and vaccines. In such industries, Bioprocesses are known by their harsh environment and very expensive physical sensors. This paper deals with nonlinear estimation and control of fed-batch Escherichia coli bioprocess. Enhancing the process performance and maximizing its efficiency by optimizing the control of Escherichia coli cultures depends on the availability of appropriate online sensors for the main culture components. In this study, an innovative method for nonlinear estimation and control of bioprocesses is designed and assessed. The new algorithm for control and estimation of Escherichia coli bioprocess states, based on the State-Dependent Riccati Equation technique, is validated by numerical simulation. The results obtained clearly demonstrate the effectiveness of the proposed technique for Biosystems in measuring, monitoring, and control of their natural nonlinear dynamics.

[1]  D. Dochain,et al.  On-Line Estimation and Adaptive Control of Bioreactors , 2013 .

[2]  Laurent Dewasme,et al.  Extended Kalman Filter Design for Acetate Estimation in E. coli Cultures , 2011 .

[3]  C. Diaz,et al.  Adaptive predictive control of dissolved oxygen concentration in a laboratory-scale bioreactor. , 1995, Journal of biotechnology.

[4]  Tayfun Çimen,et al.  Systematic and effective design of nonlinear feedback controllers via the state-dependent Riccati equation (SDRE) method , 2010, Annu. Rev. Control..

[5]  Peter S. Maybeck,et al.  Stochastic Models, Estimation And Control , 2012 .

[6]  Feng-Sheng Wang,et al.  On-line estimation of biomass and intracellular protein for recombinant Escherichia coli cultivated in batch and fed-batch modes , 2007 .

[7]  H. T. Banks,et al.  Nonlinear feedback controllers and compensators: a state-dependent Riccati equation approach , 2007, Comput. Optim. Appl..

[8]  Rimvydas Simutis,et al.  Generic model control of the specific growth rate in recombinant Escherichia coli cultivations. , 2006, Journal of biotechnology.

[9]  A C A Veloso,et al.  Monitoring of fed-batch E. coli fermentations with software sensors , 2009, Bioprocess and biosystems engineering.

[10]  P. Dieu,et al.  Simultaneous adaptive predictive control of the partial pressures of dissolved oxygen (pO2) and dissolved carbon dioxide (pCO2) in a laboratory-scale bioreactor , 1996 .

[11]  Ghizlane Hafidi Application de la commande prédictive non-linéaire à la commande de culture de bactéries Escherichia coli , 2008 .

[12]  Didier Dumur,et al.  Nonlinear Model Predictive Control applied to E. Coli Cultures , 2008 .

[13]  Isabel Rocha Model-based strategies for computer-aided operation of recombinant E. coli fermentation , 2003 .

[14]  C. A. D'Souza,et al.  A new technique for nonlinear estimation , 1996, Proceeding of the 1996 IEEE International Conference on Control Applications IEEE International Conference on Control Applications held together with IEEE International Symposium on Intelligent Contro.

[15]  Mohamed Mostefai,et al.  On estimation of unknown state variables in wastewater systems , 2009, 2009 IEEE Conference on Emerging Technologies & Factory Automation.

[16]  R. Katebi,et al.  On-line robust nonlinear state estimators for nonlinear bioprocess systems , 2012 .

[17]  Mats Åkesson,et al.  Probing Control of Glucose Feeding in Escherichia coli Cultivations , 1999 .