Scaling-up vaccine production: implementation aspects of a biomass growth observer and controller

Abstract This study considers two aspects of the implementation of a biomass growth observer and specific growth rate controller in scale-up from small- to pilot-scale bioreactors towards a feasible bulk production process for whole-cell vaccine against whooping cough. The first is the calculation of the oxygen uptake rate, the starting point for online monitoring and control of biomass growth, taking into account the dynamics in the gas-phase. Mixing effects and delays are caused by amongst others the headspace and tubing to the analyzer. These gas phase dynamics are modelled using knowledge of the system in order to reconstruct oxygen consumption. The second aspect is to evaluate performance of the monitoring and control system with the required modifications of the oxygen consumption calculation on pilot-scale. In pilot-scale fed-batch cultivation good monitoring and control performance is obtained enabling a doubled concentration of bulk vaccine compared to standard batch productio

Control and identification in activated sludge processes = Regeling en identifikatie in aktief-slib processen

This thesis is about control and identification in activated sludge processes (ASP's). The chapters in this thesis are divided in two parts. Part I deals with the development of the best feasible, close-to-optimal adaptive receding horizon optimal controller (RHOC) for N-removal in a continuously mixed alternating activated sludge process reactor. Subsequently this controller and the most common existing controllers are mutually compared by means of simulations. In addition the application of the close-to-optimal RHOC controller to a system of two hydraulically connected alternating reactors is simulated for a range of plant designs within this class. In this way the combination of design and operation is optimized. Part II concerns identification on the basis of DO-measurements and respirometry. First the DO-dynamics in a continuously mixed ASP reactor are identified, including the non-linear relation between k L a and q air . Subsequenly the dynamics of a (DO-sensor based) continuous flow respirometer are identified by exciting its dynamics.In chapter 1 the principles of the N-removing ASP are shortly explained. The new problem of total-N removal is discussed. The general features of the ASP control problem are listed: disturbance attenuation, storm events, process uncertainty and variation, multiple time-scales. Special attention is paid to the potential of RHOC. The literature with respect to operational aspects of N-removal as well as the use of DO-sensors and respirometers in ASP operation is coarsely reviewed. It is argued that the anoxic periods approach for N-removal offers two principle advantages over the anoxic zones approach: excitation of dynamics and no need for internal recirculation. Some problems in the field are indicated. With respect to DO-sensors it is illustrated that the challenges today are in the field of extracting not only DO but also additional information from its readings. All experiments in this thesis have been carried out at a pilot scale ASP. A description of this pilot plant is given in chapter 1. The chapter ends with the formulation of research objectives and the thesis outline.Chapters 2 till 5 present the design procedure for the adaptive RHOC for control of NH 4 and NO x , though not exactly chronologically. The first step is presented in chapter 4, it concerns application of optimal control to the N-removal part of the generally accepted Activated Sludge Model no. 1. From this optimal control study it occurs that alternating nitrification/denitrification, as opposed to simultaneous nitrification/denitrification, may be optimal indeed. This, together with the risk of sludge bulking at limiting DO-values, justifies the limitation to alternating process operation. To implement an optimal control strategy on-line the receding horizon principle is needed, leading to RHOC. RHOC uses an internal process model for short term predictions. Hence a computationally efficient process model is required. Such a model is developed in chapter 2 by capturing the slower process dynamics in time-varying model parameters. It is taken into account that the model structure must be suited for recursive identification of the time-varying model parameters from the measurements.RHOC, like any model predictive controller, computes the current controls on the basis of model predictions upto horizon H . Hence the sum of squared 1, 2, .., H -step ahead prediction errors is a natural identification criterion. In chapter 2 this idea is postulated and applied to NH 4 /NO x measurements collected from the pilot scale ASP described in chapter 1. H appears to affect the parameter estimates significantly, supporting the idea that use of this new identification criterion will improve MPC performance in general.In chapter 4 RHOC with this simple model is applied to the pilot plant's alternating reactor. The controller successfully passed several tests, but it also appeared that the performance of this controller is suboptimal due to inaccurate model predictions. This was to be expected, as the simplicity of the N-removal model in chapter 2 has been achieved by capturing the slower process dynamics in the model parameters, while in this stage they are not recursively estimated.The results of chapter 4 illustrate that recursive identification of (some of the) model parameters is required to keep the model uptodate. Chapter 3 presents the algorithm for recursive identification of those model parameters. The Kalman filter is used, because it has the attractive feature that the filter gain accompanying non-identifiable parameters ( e.g. the nitrification rate during anoxic periods) increases linearly in time. It is proven that this increase of the filter gain will not cause instability during normal process operation. The method performs excellently on real data.Chapter 5 concerns adaptive RHOC of N-removal in alternating ASP reactors, being the combination of the recursively identified model in chapter 3 and the RHOC controller in chapter 4. Although stability of the nonlinear RHOC feedback controller has not been proven, not to mention its combination with recursive identification, only one source of instability was encountered in many experiments. This is the scenario in which NH 4 dominates the objective functional, its setpoint is zero and the estimated rate of nitrification has become negative for whatever reason. In that case the controller will keep aeration off to prevent the predicted production of NH 4 , as a consequence no new information to update the estimated nitrification rate is obtained and the deadlock is there. Obviously this scenario is easy to prevent and does not occur under normal operating conditions.In chapter 4 the unusual observation is done that the RHOC performance is nearly invariant to its prediction horizon. This triggered a study on the cause of this phenomena and an effort to generalize the results as far as possible, the results are presented in chapter 6. It has led to the derivation of an l 1 -norm optimal state feedback controller for 2-dimensional linear time invariant systems with decoupled dynamics and a single control input.In chapter 7 the close-to-optimal adaptive RHOC of chapter 5 and three existing control strategies (timers, NH 4 -bounds based and ORP, Oxidation Reduction Potential, based) for N-removal in continuously mixed alternating reactors are compared by means of simulation. The simulations are carried out in SIMBA TM, a commercially available application within the MATLAB/SIMULINK TMenvironment, based on the Activated Sludge Model no. 1. Drawback of simulations is that the dynamics of both the sensors and the process need to be modelled. And even the best model of the ASP is nothing but a poor resemblance of the real process. However, a fair experimental comparison of multiple controllers is impossible, not only for financial reasons. Simultaneous experimental testing would require the availability of multiple identical plants in parallel. Sequential testing on one plant would disrupt the results by changes in process conditions and influent, disabling a mutual comparison. Hence simulation is the best way to compare different control-schemes. It appears that three totally different controllers (timers, NH 4 -bounds based and adaptive RHOC) can achieve a more or less equal performance, if tuned optimally. Adaptive RHOC turns out to be superior in terms of sensitivity to suboptimal tunings. The timers approach is attractive for its simplicity, but very sensitive to suboptimal tuning.Chapter 8 describes a simulation study with the scope to optimise the plant design and operation strategy of alternating activated sludge processes for N-removal with two hydraulically connected reactors. The methodology is to simulate the application of RHOC to a range of different plant designs within this class of systems. The RHOC algorithm is obtained by reformulating the controller of chapter 4 for a 2-reactors system. It appears that in the optimal process design the two reactors are placed in series, the first reactor is about four times as large as the second one. A conceptually simple feedback controller straightforwardly implements the improved operation strategy. The results of this chapter strongly advocate the simulation of optimal control applied to complex process models. The results are unexpected and indicate a significant outperformance of the current operation strategy. This kind of simulation studies at least serves as an ideas generator.Chapter 9 presents a grey-box modelling approach for the identification of the nonlinear DO dynamics. Herein, singular value decomposition of the locally available Jacobian matrix, or equivalently eigenvalue decomposition of the parameter covariance matrix, as well as parameter transformation are essential techniques. The use of respiration rate measurements greatly simplifies the modelling procedure. The approach is amongst others capable of identifying the non-linear function k L a ( q air ), i.e. the relationship between k L a and the aeration input signal q air . This is especially valuable in experimental identification of the relationship between k L a ( q air ) and the design of (newly developed) aeration equipment, the use of specific carrier materials in aerated reactors, or the presence of certain detergents. After all a higher k L a at a given q air results in a higher efficiency of energy usage for aeration, and hence identification of k L a ( q air ) for newly developed equipment can yield important sales arguments.Chapters 10 and 11 both deal with excitation of the respiration chamber dynamics in a continuous flow respirometer with the objective to extract additional information from its dissolved oxygen (DO) sensor readings. Chapter 10 is an effort to improve the accuracy of the BOD st -estimation technique developed by Spanjers et al . (1994). Contrary to expectation, the estimates still suffer from unacceptable inaccuracy due to large parameter correlation. However, a slight modification in the measurement strategy is proposed which is expected to enable more accurate estimation. The results of experiments with this modified measurement strategy are reported in chapter 11. The estimation results convincingly discourage further efforts to identify sludge kinetics and BOD st from this type of experiments.The two other objectives of chapter 11 are the identification of the DO-sensor dynamics and the dilution rate in a continuous flow respirometer by excitation of the respiration chamber dynamics. Two separate simple procedures are presented. Both procedures consist of on-purpose in-sensor experiments succeeded by an ordinary least squares estimation step. The feasibility of both procedures is verified in experiments with activated sludge, fed with municipal wastewater. Large experimental data sets are presented, which strongly advocate the on-line incorporation of both procedures in the everyday operation of the respirometer.In chapter 12 those conclusions drawn in the individual chapters which are of direct relevance to practitioners are summarized. Moreover some remaining ideas, which I believe are novel and likely to be succesfull, are shortly expounded in chapter 12 as well. The ideas concern: 1) Meeting N-total effluent standards by permitting elevated effluent NH 4 ; 2) Control explicitly aiming at meeting yearly averaged effluent standards; 3) The use of pH-measurements for continuous on-line tuning of timers in a timer-based operation strategy for alternating N-removal in a continuously mixed ASP reactor.</p

Instrumentation and control of anaerobic digestion processes: a review and some research challenges

The final publication is available at Springer via http://dx.doi.org/10.1007/s11157-015-9382-6[EN] To enhance energy production from methane or resource recovery from digestate, anaerobic digestion processes require advanced instrumentation and control tools. Over the years, research on these topics has evolved and followed the main fields of application of anaerobic digestion processes: from municipal sewage sludge to liquid mainly industrial then municipal organic fraction of solid waste and agricultural residues. Time constants of the processes have also changed with respect to the treated waste from minutes or hours to weeks or months. Since fast closed loop control is needed for short time constant processes, human operator is now included in the loop when taking decisions to optimize anaerobic digestion plants dealing with complex solid waste over a long retention time. Control objectives have also moved from the regulation of key variables measured online to the prediction of overall process perfor- mance based on global off-line measurements to optimize the feeding of the processes. Additionally, the need for more accurate prediction of methane production and organic matter biodegradation has impacted the complexity of instrumentation and should include a more detailed characterization of the waste (e.g., biochemical fractions like proteins, lipids and carbohydrates)andtheirbioaccessibility andbiodegradability characteristics. However, even if in the literature several methodologies have been developed to determine biodegradability based on organic matter characterization, only a few papers deal with bioaccessibility assessment. In this review, we emphasize the high potential of some promising techniques, such as spectral analysis, and we discuss issues that could appear in the near future concerning control of AD processes.The authors acknowledge the financial support of INRA (the French National Institute for Agricultural Research), the French National Research Agency (ANR) for the "Phycover" project (project ANR-14-CE04-0011) and ADEME for Inter-laboratory assay financial support.Jimenez, J.; Latrille, E.; Harmand, J.; Robles Martínez, Á.; Ferrer Polo, J.; Gaida, D.; Wolf, C.... (2015). Instrumentation and control of anaerobic digestion processes: a review and some research challenges. Reviews in Environmental Science and Biotechnology. 14(4):615-648. doi:10.1007/s11157-015-9382-6S615648144Aceves-Lara CA, Latrille E, Steyer JP (2010) Optimal control of hydrogen production in a continuous anaerobic fermentation bioreactor. 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Implementation of a specific rate controller in a fed-batch E. coli fermentation

The specific growth rate is one of the most important process variables characterizing the state of microorganisms during fermentations mainly because the biosynthesis of many products of interest is often related with the values assumed by this parameter. In the particular case of the fed-batch operation of Escherichia coli for the production of recombinant proteins, it is important to maintain the specific growth rate below a certain threshold in order to avoid the accumulation of acetic acid throughout the fermentation and, additionally, it is often argued that both pre- and the post-induction specific growth rates should be closely controlled in order to achieve maximum productivities of the desired recombinant protein. In a previous work the authors have developed and validated by simulations a strategy for the automatic control of the specific growth rate in E. coli fed-batch fermentations based on an asymptotic observer for biomass and on developed estimators for the specific growth rates. The main purpose of the present work was to implement experimentally the developed observer, estimator and controller in a real fed-batch fermentation process. For that purpose a data acquisition and control program was developed in LabVIEW that allows the acquisition of the necessary on line data (off gas and dissolved oxygen concentration and culture weight) and the calculation of the feeding rates using the developed equations. The feedforward-feedback controller developed was able to keep the culture growing in an exponential phase throughout the fermentation without accumulation of glucose and acetate.Fundação para a Ciência e a Tecnologia (FCT) - RecSysBio projecto POCI/BIO/60139/200

Enhancement of anaerobic digestion of actual industrial wastewaters : reactor stability and kinetic modeling.

Industrial plants pay disposal costs for discharging their wastewater that can contain pollutants, toxic organics and inorganics, to the sewer based on the Biological Oxygen Demand (BOD) or Chemical Oxygen Demand (COD) of the streams. It has become increasingly expensive for industry to meet stringent regulatory standards. One solution to reduce this cost is to anaerobically degrade the COD content, which in turn generates useful methane gas that can be used to generate useful energy or heat. Anaerobic Digestion (AD) is one of the most suitable renewable resources of conversion of industrial wastewaters to bioenergy, but it is not widely utilized in the US. As a result, this research focused on understanding and improving fundamental technical and economic obstacles such as long residence times, large reactor sizes/footprints and product quality that hamper its industrial applications in the US. Kinetic modeling of these anaerobic digestion processes is important for evaluating experimental results, predicting performance, and optimizing reactor designs, but the modeling can be especially difficult for complex wastewater compositions. Respirometry tests were first conducted to assess the impact of substrate loading on kinetic parameters during AD of three industrial/agricultural wastewaters: soybean processing WW, brewery WW, and recycled beverage WW. Results showed that the rate order statistically increased with increasing initial COD content, demonstrating that conventional kinetic modeling is inadequate for these WW of complex composition. COD degradation models revealed the Monod model gave the best overall fit to experimental data throughout the duration of the AD process, but the reactions were best fit to first-order kinetics during the first 7-9 hours and then best fit to higher order kinetics after about 8-13 hours depending on initial COD load. Expanded granular sludge bed (EGSB) reactors are two-stage continuous systems developed to reduce the residence time and footprint by expanding the sludge bed and escalating hydraulic mixing. However, higher molecular weight and slowly degrading organics, such as crude proteins and fats, cannot efficiently diffuse into the granular biomass to be digested before exiting the reactor, which limits AD efficiency. COD removal efficiency increased by up to 42% and biogas production rate by up to 32% for equivalent organic loading rates by properly manipulating COD load and feed rate. Hydrogen gas, an intermediate product generated during stage-one pre-acidification (PA), escapes the PA tank but theoretically can be captured and sent to the second stage EGSB reactor to enhance the biogas quality by biologically converting the carbon dioxide to methane. Introducing supplemental hydrogen gas in amounts less than theoretically generated in the PA tank increased energy yield by up to 42% and enhanced biogas quality by up to 20%. In addition, COD removal efficiency remained constant at ~98%, indicating that hydrogen injection did not negatively affect overall substrate removal

Nonlinear model of leachate anaerobic digestion treatment process

In this report a continuous adaptive high−gain observer method is presented for the estimation of state variables that could not be measurable online and unknown time−varying parameters of leachate anaerobic digestion treatment process. The high−gain observer is a variant of the Luenberger extended observer and involves an adjustable gain parameter. It is characterized by easy implementation and calibration, is stable and exhibit exponential convergence. The observer is based on a simplified mathematical model of the system. Calibration of the model was performed with real data from the Upflow Anaerobic Sludge Blanket (UASB) reactor for landfill leachate treatment in open loop under normal operational conditions. The model performance is evaluated via numerical simulations showing adequate results. The criteria used for considering the model as acceptable is to calculate the values of Mean Magnitude of Relative Error (MMRE) and Prediction at level l.Peer reviewe

Modelling concentration gradients in fed‐batch cultivations of E. coli – towards the flexible design of scale‐down experiments

BACKGROUND: The impact of concentration gradients in large industrial-scale bioreactors on microbial physiology can be studied in scale-down bioreactors. However, scale-down systems pose several challenges in construction, operation and footprint. Therefore, it is challenging to implement them in emerging technologies for bioprocess development, such as in high throughput cultivation platforms. In this study, a mechanistic model of a two-compartment scale-down bioreactor is developed. Simulations from this model are then used as bases for a pulse-based scale-down bioreactor suitable for application in parallel cultivation systems. RESULTS: As an application, the pulse-based system model was used to study the misincorporation of non-canonical branched-chain amino acids into recombinant pre-proinsulin expressed in Escherichia coli, as a response to oscillations in glucose and dissolved oxygen concentrations. The results show significant accumulation of overflow metabolites, up to 18.3 % loss in product yield and up to 10 fold accumulation of the non-canonical amino acids norvaline and norleucine in the product in the pulse-based cultivation, compared to a reference cultivation. CONCLUSIONS: Our results indicate that the combination of a pulse-based scale-down approach with mechanistic models is a very suitable method to test strain robustness and physiological constraints at the early stages of bioprocess development.EC/H2020/643056/EU/Rapid Bioprocess Development/Biorapi