Adaptive nonlinear regulation of fed-batch biological reactors: an industrial application

The authors present a general methodology for the design of adaptive regulators for fed-batch biological reactors with the aid of an illustrative case study which has given rise to a genuine industrial application. The application under consideration is the feedback optimization of yeast fermentations, which are of particular interest because yeasts are among the most frequently used microorganisms in genetic engineering for the production of high added value metabolites. The case study is representative of a wide class of control problems in biotechnology where the regulation of some substrate or metabolite concentration helps to solve yield/productivity conflicts.<<ETX>>

[1]  T. Yamane,et al.  Application of porous teflon tubing method to automatic fed‐batch culture of microorganisms II. Automatic constant‐value control of fed substrate (ethanol) concentration in semibatch culture of yeast , 1981 .

[2]  Suteaki Shioya,et al.  Maximum production in a bakers' yeast fed‐batch culture by a tubing method , 1981 .

[3]  K C Chen,et al.  On‐line optimal control for fed‐batch culture of baker's yeast production , 1985, Biotechnology and bioengineering.

[4]  B Sonnleitner,et al.  Growth of Saccharomyces cerevisiae is controlled by its limited respiratory capacity: Formulation and verification of a hypothesis , 1986, Biotechnology and bioengineering.

[5]  Marie-Noëlle Pons,et al.  Influence of acetate on growth kinetics and production control of Saccharomyces cerevisiae on glucose and ethanol , 1986, Applied Microbiology and Biotechnology.

[6]  D Williams,et al.  On‐line adaptive control of a fed‐batch fermentation of Saccharomyces cerevisiae , 1986, Biotechnology and bioengineering.

[7]  David G. Taylor,et al.  Adaptive Regulation of Nonlinear Systems with Unmodeled Dynamics , 1988, 1988 American Control Conference.

[8]  A. Isidori,et al.  Adaptive control of linearizable systems , 1989 .

[9]  Jan Peter Axelsson,et al.  Modelling and Control of Fermentation Processes , 1989 .

[10]  M.N. Pons,et al.  Comparison between Adaptive and Model-Based Extended Kalman Filters , 1989, 1989 American Control Conference.

[11]  Per Hagander,et al.  Substrate Control of Biotechnical Fedbatch Processes. Robustness and the Role of Adaptivity , 1990 .

[12]  G. Bastin,et al.  Reduced order dynamical modelling of reaction systems: A singular perturbation approach , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.

[13]  G. Bastin,et al.  Adaptive Stabilization of Nonlinear-systems , 1991 .