Mihaela Sbarciog

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. The latter is a classical optimal control problem, which can be solved using the maximum principle of Pontryagin. The proposed control law is of the bang–bang type. The process is driven from an initial state to a small neighborhood of the optimal steady state by switching the manipulated variable (dilution rate) from the minimum to the maximum value at a certain time instant. Then the dilution rate is set to the optimal value and the system settles down in the optimal steady state. This control law ensures the convergence of the system to the optimal steady state and substantially increases its stability region. The region of attraction of the steady state corresponding to maximum production of methane is considerably enlarged. In some cases, which are related to the possibility of selecting the minimum dilution rate below a certain level, the stability region of the optimal steady state equals the interior of the state space. Aside its efficiency, which is evaluated not only in terms of biogas production but also from the perspective of treatment of the organic load, the strategy is also characterized by simplicity, being thus appropriate for implementation in real-life systems. Another important advantage is its generality: this technique may be applied to any anaerobic digestion process, for which the acidogenesis and methanogenesis are, respectively, characterized by Monod and Haldane kinetics.

On the Optimization of Biogas Production in Anaerobic Digestion Systems

Abstract This paper presents a strategy for the optimization of biogas outflow rate in an anaerobic digestion process described by a two-population model. The methodology relies on the solution of two optimization problems: steady state optimization for determining the optimal operating point and transient optimization. The latter is solved using the maximum principle of Pontryagin. The proposed control law, which drives the process from an initial state to the optimal steady state while maximizing the biogas outflow rate, consists of switching the manipulated variable (dilution rate) from the minimum to the maximum value and then to the optimal value at well defined instants. This control law substantially increases the stability region of the optimal equilibrium point, enlarging it in some cases to almost the entire state space. Aside its efficiency, the strategy is also characterized by simplicity, being thus appropriate for implementation in real-life systems. Another important advantage is its generality: this technique may be applied to any anaerobic digestion process, for which the acidogenesis and methanogenesis are respectively characterized by Monod and Haldane kinetics.

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. Simulation results demonstrate the approach potentiality.

A Biogas-Based Switching Control Policy for Anaerobic Digestion Systems

This paper presents a simple switching control policy for driving an anaerobic digestion system from an arbitrary initial state to an optimal setpoint, characterized by the maximum biogas production. A high wastewater treatment efficiency is achieved and a fast convergence to the optimal setpoint is obtained. The main features of this control strategy are its simplicity and ease of implementation, as it is based on the measurement of the biogas outflow rate, which is commonly available in anaerobic digestion systems.

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. The second is an asymptotic observer, which provides one of the two biomass concentrations, whereas the third is a super-twisting observer for one of the input concentrations and the second biomass concentration.

Some Considerations About Control of Multispecies Anaerobic Digestion Systems

Abstract This paper presents a brief evaluation of a start-up strategy for multispecies anaerobic digestion systems modelled as two-step reaction systems, in which acidogenesis is described by Monod kinetics while the methanogenesis is described by Haldane kinetics. The start-up policy has been developed originally for single species systems with the aim of maximizing the biogas outflow rate. It consists of switching the dilution rate from minimum to maximum and then to the optimal value in order to bring the system from an arbitrary initial condition to the optimal setpoint. This start-up strategy is applied to the multispecies system using an averaged model, which is usually the only model that can be identified for a multispecies system, as measuring individual biomasses is quite difficult in practice. This study shows that the start-up policy leads to an efficient ecosystem, characterized by high outflow rate of biogas, even in the case of an inaccurate averaged model. It can be viewed as a robustness evaluation of the single species start-up strategy, as the process changes from the averaged kinetics to the kinetics of the winning species during species selection.

A Cascade MPC-Feedback Linearizing Strategy for the Multivariable Control of Animal Cell Cultures

Abstract In this study, a multivariable control structure is developed to simultaneously control the concentrations of cells and of one of the nutrients in an animal cell cultivation system operated in perfusion. A cascade control structure is considered consisting of (i) an inner loop with a partially linearizing feedback controller, tuned so as to ensure robustness with respect to parameter uncertainties and non-canceled nonlinearities; and (ii) an outer loop involving two linear predictive controllers. The resulting control strategy shows robustness and performance properties similar to more computationally demanding strategies (such as a multivariable nonlinear MPC strategy), while requiring less measurements and involving an easier implementation.

An Adaptive Cascade Structure for the Estimation and Control of Perfusion Animal Cell Cultures

This paper presents an effective and robust structure for the estimation and control of perfusion cell cultures, in which the cells and glucose concentrations are simultaneously controlled by manipulating the dilution and bleed rates. Firstly, a partially linearizing feedback controller is designed to ensure an approximately linear decoupled dynamics between the controlled outputs and the manipulated inputs. Then the model of the inner loop is used to design an extended Kalman filter, which estimates all the system states used in the implementation of the linearizing feedback control law from the (possibly noisy) measurements of cells and glucose concentrations. Two PI controllers are used in the outer loop for a good tracking performance, which are tuned using a receding horizon optimization procedure. The proposed structure shows good performance and robustness with respect to parameter uncertainties, non-cancelled nonlinearities and measurement noise.

Evaluation of Steady State Multiplicity for the Anaerobic Degradation of Solid Organic Waste

Abstract This paper evaluates the number and stability of steady states of a two-population model, describing the anaerobic degradation of solid organic waste. Analytical conditions are provided, which define in the input space regions characterized either by a different number or change of stability of steady states. The qualitative results do not depend on the parameter values and allow the proper selection of inputs and initial conditions to achieve a good operation of the process.

Start-up of multi-species anaerobic digestion systems: extrapolation of the single species approach

This paper presents a brief evaluation of a start-up strategy for multi-species anaerobic digestion systems modelled as two-step reaction systems, where acidogenesis is described by Monod kinetics while the methanogenesis is described by Haldane kinetics. The start-up policy has been developed originally for single species systems with the aim of maximizing the biogas outflow rate. It consists of switching the dilution rate from minimum to maximum and then to the optimal value (bang-bang control) in order to bring the system from an arbitrary initial condition to the optimal set-point. This start-up strategy is applied to the multi-species system using an averaged model, which is usually the only model that can be identified for a multi-species system, as measuring individual biomasses is almost impossible in practice. Even the development of an accurate averaged model, fully characterizing the system dynamics based on the variation of the species proportions is difficult. The averaged models used in this study are built based on a more or less accurate knowledge of the species proportions and their kinetics at the start-up instant and used as such in the application of the start-up policy. It is shown that the start-up policy leads to an efficient ecosystem, characterized by high outflow rate of biogas, which is very close to the maximum even in the case of an inaccurate averaged model. The influence of the model accuracy on the system stability and its productivity is discussed. This study can also be viewed as a robustness evaluation with respect to model inaccuracy of the single species start-up strategy, as the process changes from the averaged kinetics to the kinetics of the winning species during species selection.