Sergio Valentinotti

Optimal operation of fed-batch fermentations via adaptive control of overflow metabolite

The maximization of biomass productivity in the fed-batch fermentation of Saccharomyces cerevisiae is analyzed. Due to metabolic bottleneck, often attributed to limited oxygen capacity, ethanol is formed when the substrate concentration is above a critical value, which results in a decrease in biomass productivity. Thus, to maximize the production of biomass, the substrate concentration should be kept at the critical value. However, this value is unknown a priori and may change from experiment to experiment. A way to overcome this lack of knowledge is to allow the cells to produce a very small amount of ethanol. This way, the problem of maximizing the production of biomass is converted into that of regulating the concentration of ethanol, for which cell growth can be viewed as a perturbation. A novel adaptive control methodology based on the internal model principle is used to maintain the desired ethanol setpoint and reject the perturbation. Only a single parameter needs to be estimated on-line. Experimental results demonstrate the effectiveness of the proposed control methodology.

Know-how and know-why in biochemical engineering

This contribution analyzes the position of biochemical engineering in general and bioprocess engineering particularly in the force fields between fundamental science and applications, and between academia and industry. By using culture technology as an example, it can be shown that bioprocess engineering has moved slowly but steadily from an empirical art concerned with mainly know-how to a science elucidating the know-why of culture behavior. Highly powerful monitoring tools enable biochemical engineers to understand and explain quantitatively the activity of cellular culture on a metabolic basis. Among these monitoring tools are not just semi-online analyses of culture broth by HPLC, GC and FIA, but, increasingly, also noninvasive methods such as midrange IR, Raman and capacitance spectroscopy, as well as online calorimetry. The detailed and quantitative insight into the metabolome and the fluxome that bioprocess engineers are establishing offers an unprecedented opportunity for building bridges between molecular biology and engineering biosciences. Thus, one of the major tasks of biochemical engineering sciences is not developing new know-how for industrial applications, but elucidating the know-why in biochemical engineering by conducting research on the underlying scientific fundamentals.

An identification-for-control procedure with robust performance

A data-driven controller design procedure is proposed in this paper. The controller is based on both an estimated plant model and its estimated uncertainty described by an ellipsoid in parameter space. Desired performance is specified by the speed and the damping of the modeled response. The unmodeled response is rejected by requiring robust performance with respect to a generalized stability region. Moreover, estimation of a disturbance model enables further rejection of the unmodeled response. The methodology is applied to a nonlinear and unstable magnetic suspension system. High performance is achieved for various specifications over a large operational range.

An Optimal Operating Strategy for Fed-Batch Fermentations by Feeding the Overflow Metabolite

Keywords: Bioreactor ; overflow mechanism ; optimization Reference LA-CONF-2004-026 Record created on 2004-11-26, modified on 2016-08-08

Modeling for Control of Fed-Batch Fermenters

Abstract A simple method for controlling fed-batch fermenters is presented. Two linear models are derived for control design. The first one relates the input to the desired operating point. The second model describes the exponential cell growth as an unstable disturbance. This way, the desired operation is easily implemented by adaptively rejecting the disturbance. As a result, the specific cell growth rate can be estimated on-line. Simulation results are presented.