Estimation and control of non-linear variables in a continuous fermentation process using sliding mode techniques

Biomass, substrate or metabolite concentrations are difficult to measure online in fermentation processes because of the lack of reliable, cheap and sterilizable transducers. Currently, many of the measurements required may be determined through offline analysis, which is costly and time consuming. Furthermore, the specific growth rate conditions involved in the fermentation are typically non-linear and uncertain. In this paper, a new variable, the substrate consumption rate, consisting of a combination of substrate concentration, biomass concentration, specific growth rate and yield production coefficient, is introduced to overcome these problems and simplify the non-linear differential equations of the fermentation process. A sliding mode observer, which only requires measurement of substrate concentration, is then developed to solve the estimation problem, providing a soft sensor to estimate the substrate consumption rate. It is shown that the sliding mode exhibited by the corresponding observer error dynamics is exponentially stable. This parameterization and the resulting estimate of biomass concentration are then utilized within a feedback control strategy. Non-linear simulation results in the presence of both parameter uncertainties and external disturbances illustrate the approach.