Control and estimation of anaerobic digestion processes using hydrogen and volatile fatty acids measurements.

The anaerobic digestion (AD) technology is widely used in the treatment of waste and wastewater. To ensure the treatment efficiency and to increase the production of biogas, which can be reused as a renewable energy source, a good understanding of the process and tight control are needed. This paper presents an estimation and control scheme, which can be successfully used in the operation of the AD process.

On the derivation of a simple dynamic model of anaerobic digestion including the evolution of hydrogen.

Hydrogen has been found to be an important intermediate during anaerobic digestion (AD) and a key variable for process monitoring as it gives valuable information about the stability of the reactor. However, simple dynamic models describing the evolution of hydrogen are not commonplace. In this work, such a dynamic model is derived using a systematic data driven-approach, which consists of a principal component analysis to deduce the dimension of the minimal reaction subspace explaining the data, followed by an identification of the kinetic parameters in the least-squares sense.

Application of super-twisting observers to the estimation of state and unknown inputs in an anaerobic digestion system.

This paper presents the estimation of the unknown states and inputs of an anaerobic digestion system characterized by a two-step reaction model. The estimation is based on the measurement of the two substrate concentrations and of the outflow rate of biogas and relies on the use of an observer, consisting of three parts. The first is a generalized super-twisting observer, which estimates a linear combination of the two input concentrations.

Accelerating animal cell growth in perfusion mode by multivariable control: simulation studies.

This study considers the problem of manipulating in an optimal way the perfusion and bleed flow rates of a continuous culture of hybridoma cells, so as to achieve a fast transient start-up and reject potential disturbances. The proposed solution makes use of an analysis of the properties of the steady state solutions of the nonlinear dynamic model of the cell culture, and in particular the relationship between the two main limiting substrates, glucose and glutamine. The solution is implemented using extended prediction self-adaptive control.

An optimizing start-up strategy for a bio-methanator.

This paper presents an optimizing start-up strategy for a bio-methanator. The goal of the control strategy is to maximize the outflow rate of methane in anaerobic digestion processes, which can be described by a two-population model. The methodology relies on a thorough analysis of the system dynamics and involves the solution of two optimization problems: steady-state optimization for determining the optimal operating point and transient optimization.