Fuzzy control of ethanol concentration its application to maximum glutathione production in yeast fed-batch culture

A fuzzy logic controller (FLC) for the control of ethanol concentration was developed and utilized to realize the maximum production of glutathione (GSH) in yeast fedbatch culture. A conventional fuzzy controller, which uses the control error and its rate of change in the premise part of the linguistic rules, worked well when the initial error of ethanol concentration was small. However, when the initial error was large, controller overreaction resulted in an overshoot.An improved fuzzy controller was obtained to avoid controller overreaction by diagnostic determination of "glucose emergency states" (i.e., glucose accumulation or deficiency), and then appropriate emergency control action was obtained by the use of weight coefficients and modification of linguistic rules to decrease the overreaction of the controller when the fermentation was in the emergency state. The improved fuzzy controller was able to control a constant ethanol concentration under conditions of large initial error.The improved fuzzy control system was used in the GSH production phase of the optimal operation to indirectly control the specific growth rate mu to its critical value mu(c). In the GSH production phase of the fed-batch culture, the optimal solution was to control mu to mu(c) in order to maintain a maximum specific GSH production rate. The value of mu(c) also coincided with the critical specific growth rate at which no ethanol formation occurs. Therefore, the control of mu to mu(c) could be done indirectly by maintaining a constant ethanol concentration, that is, zero net ethanol formation, through proper manipulation of the glucose feed rate. Maximum production of GSH was realized using the developed FLC; maximum production was a consequence of the substrate feeding strategy and cysteine addition, and the FLC was a simple way to realize the strategy. (c) 1993 John Wiley & Sons, Inc.     

Nonlinear control of bioreactors with input multiplicities—an experimental work

The phrase input multiplicities means that an input variable with more than one value produces the same output value as if there were a single input–single output process. With input multiplicities, the value of the process gain changes as the manipulated variable changes, and beyond a certain input value, the sign of the gain also changes. A conventional PI controller for processes with input multiplicities may give unstable, less economical, or oscillatory responses. In the present work, control problems of a continuous bioreactor exhibiting two input multiplicities in the dilution rate on productivity were experimentally analyzed. A regulatory problem for the evaluation of controllers was taken up, i.e. a step change was made in the feed substrate concentration from 20 to 25 g/l at steady state conduction at lower (0.09386 h⁻¹) and higher (0.2278 h⁻¹) dilution rates for the same productivity of 2.9 g/l h. The nonlinear PI controller gave a more stable and fast response at both input dilution rates. The linear PI controller designed for a lower input dilution rate was stable, with some oscillations at the lower dilution rate, but the response was unstable at a higher dilution rate due to the input multiplicity behaviour of the process. Thus, nonlinear PI controller performance was found to be superior to that of the linear controller, and earlier reported theoretical results have been validated by the present experimental work.     

Unstable steady state operations of substrate inhibited cultures by dissolved oxygen control

Microorganism kinetic growth characterized by substrate inhibition was investigated by means of a continuous stirred tank reactor equipped with a feedback controller of the medium feeding flow rate. The aerobic growth of Pseudomonas sp. OX1 with phenol as carbon/energy source was adopted as a case study to test a new control strategy using dissolved oxygen concentration as a state variable. The controller was successful in steadily operating bioconversion under intrinsically unstable conditions. A simple model of the controlled system was proposed to set the feedback controller. The specific growth rate of Pseudomonas sp. OX1 was successfully described by means of the Haldane model. The regression of the experimental data yielded μ(M)=0.26 h(-1), K(Ph)=5×10(-3)g/L and K(I)=0.2g/L. The biomass-to-substrate fractional yield as a function of the specific growth rate did not change moving from substrate-inhibited to substrate-deficient state. The data was modelled according to the Pirt model: m=1.7×10(-2)g/(gh), Y(X/Ph)(Th)=1.3g/g. The specific growth rates calculated for batch and continuous growth were compared.     

An intelligent control method based on fuzzy logic for a robotic testing system for the human spine

In previous biomechanical studies of the human spine, we implemented a hybrid controller to investigate load-displacement characteristics. We found that measurement errors in both position and force caused the controller to be less accurate than predicted. As an alternative to hybrid control, a fuzzy logic controller (FLC) has been developed and implemented in a robotic testing system for the human spine. An FLC is a real-time expert system that can emulate part of a human operator's knowledge by using a set of action rules. The FLC provides simple but robust solutions that cover a wide range of system parameters and can cope with significant disturbances. It can be viewed as a heuristic and modular way of defining a nonlinear, table-based control system. In this study, an FLC is developed which uses the force difference and the change in force difference as the input parameters, and the displacement as the output parameter. A rule-table based on these parameters is designed for the controller Experiments on a physical model composed of springs demonstrate the improved performance of the proposed method.     

Inhibition kinetics of phenol degradation from unstable steady-state data

Multiplicity of steady states of a continuous culture with an inhibitory substrate was used to estimate kinetic parameters under steady-state conditions. A continuous culture of Pseudomonas cepacia G4, using phenol as the sole source of carbon and energy, was overloaded by increasing the dilution rate above the critical dilution rate. The culture was then stabilized in the inhibitory branch by a proportional controller using the carbon dioxide concentration in the reactor exhaust gas as the controlled variable and the dilution rate as the manipulated variable. By variation of the set point, several unstable steady states in the inhibitory branch were investigated and the specific phenol conversion rates calculated. In addition, phenol degradation was investigated under substrate limitation (chemostat operation).The results show that the phenol degradation by P. cepacia can be described by the same set of inhibition parameters under substrate limitation and under high substrate concentrations in the inhibitory branch. Biomass yield and maintenance coefficients were identical. Fitting of the data to various inhibition models resulted in the best fit for the Yano and Koga equation. The well-known Haldane model, which is most often used to describe substrate inhibition by phenol, gave the poorest fit. The described method allows a precise data estimation under steady-state conditions from the maximum of the biological reaction rate up to high substrate concentrations in the inhibitory branch. Inhibition parameter estimation by controlling unstable steady states may thus be useful in avoiding discrepancies between data generated by batch runs and their application to continuous cultures which have been often described in the literature. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 54: 567-576, 1997.     

Application of a fuzzy logic control system for continuous anaerobic digestion of low buffered, acidic energy crops as mono-substrate

A fuzzy logic control (FLC) system was developed at the Hamburg University of Applied Sciences (HAW Hamburg) for operation of biogas reactors running on energy crops. Three commercially available measuring parameters, namely pH, the methane (CH4) content, and the specific gas production rate (spec. GPR = m(3)/kg VS/day) were included. The objective was to avoid stabilization of pH with use of buffering supplements, like lime or manure. The developed FLC system can cover most of all applications, such as a careful start-up process and a gentle recovery strategy after a severe reactor failure, also enabling a process with a high organic loading rate (OLR) and a low hydraulic retention time (HRT), that is, a high throughput anaerobic digestion process with a stable pH and CH4 content. A precondition for a high load process was the concept of interval feeding, for example, with 8 h of interval. The FLC system was proved to be reliable during the long term fermentation studies over 3 years in one-stage, completely stirred tank reactors (CSTR) with acidic beet silage as mono-input (pH 3.3-3.4). During fermentation of the fodder beet silage (FBS), a stable HRT of 6.0 days with an OLR of up to 15 kg VS/m(3)/day and a volumetric GPR of 9 m(3)/m(3)/day could be reached. The FLC enabled an automatic recovery of the digester after two induced severe reactor failures. In another attempt to prove the feasibility of the FLC, substrate FBS was changed to sugar beet silage (SBS), which had a substantially lower buffering capacity than that of the FBS. With SBS, the FLC accomplished a stable fermentation at a pH level between 6.5 and 6.6, and a volatile fatty acid level (VFA) below 500 mg/L, but the FLC had to interact and to change the substrate dosage permanently. In a further experiment, the reactor temperature was increased from 41 to 50 degrees C. Concomitantly, the specific GPR, pH and CH4 dropped down. Finally, the FLC automatically enabled a complete recovery in 16 days.     

The performance of serial bioreactors in rapid continuous production of ethanol from dilute-acid hydrolyzates using immobilized cells

The performance of single, and series of, continuous stirred-tank (CSTBR) and fluidized-bed bioreactor (FBBR) in anaerobic continuous cultivation of glucose in defined media and dilute-acid hydrolyzates at dilution rates 0.22, 0.43, 0.65 and 0.86 h(-1) using immobilized Saccharomyces cerevisiae CBS 8066, was investigated. While the single CSTBR and FBBR could not take up more than 77% and 92% of glucose in a defined medium at dilution rate 0.86 h(-1), addition of the second bioreactor decreased the residual glucose to less than 1.1% of the incoming sugar. A similar trend was obtained in cultivation of dilute-acid hydrolyzates. A CSTBR could take up 75% and 54% of the initial fermentable sugars at dilution rates 0.43 and 0.86 h(-1), while the addition of the FBBR improved the assimilation of the sugars to 100% and 86%, respectively. The ethanol yields from the hydrolyzate were between 0.41 and 0.48 g/g in all the experiments. The specific and volumetric ethanol productivities were 1.13 g/gh and 5.98 g/Lh for the single bioreactor and 0.98 g/gh and 5.49 g/Lh for the serial bioreactor at the highest dilution rate, respectively. Glycerol was the only important by-product in terms of concentration, and yielded 0.05-0.07 g/g from the hydrolyzate. From the initial 3.98 g/L acetic acid present in the hydrolyzate, 0.1-0.8 g/L was assimilated by the cells. The yeast cells were accumulated close to the surface of the beads. While the cells had a dry-weight concentration of 129 g/L close to the surface of the beads, the concentration in the core was only 13 g/L.     

Control of continuous fed-batch fermentation process using neural network based model predictive controller

Cell growth and metabolite production greatly depend on the feeding of the nutrients in fed-batch fermentations. A strategy for controlling the glucose feed rate in fed-batch baker’s yeast fermentation and a novel controller was studied. The difference between the specific carbon dioxide evolution rate and oxygen uptake rate (Q _c − Q _o) was used as controller variable. The controller evaluated was neural network based model predictive controller and optimizer. The performance of the controller was evaluated by the set point tracking. Results showed good performance of the controller.     

Simple digital control of cell mass in turbidostat

Summary The application of simple digital control method to the control of cell mass in a continuous stirred tank bioreactor (CSTBR) was experimentally examined. This algorithm based on the time-varying bilinear predictor model was as simple as proportional-integral-derivative(PID) control algorithm and showed better performance.     

Bioprocess control from a multivariate process trajectory

A multivariate bioprocess control approach, capable of tracking a pre-set process trajectory correlated to the biomass or product concentration in the bioprocess is described. The trajectory was either a latent variable derived from multivariate statistical process monitoring (MSPC) based on partial least squares (PLS) modeling, or the absolute value of the process variable. In the control algorithm the substrate feed pump rate was calculated from on-line analyzer data. The only parameters needed were the substrate feed concentration and the substrate yield of the growth-limiting substrate. On-line near-infrared spectroscopy data were used to demonstrate the performance of the control algorithm on an Escherichia coli fed-batch cultivation for tryptophan production. The controller showed good ability to track a defined biomass trajectory during varying process dynamics. The robustness of the control was high, despite significant external disturbances on the cultivation and control parameters.     

Feed rate control in fed‐batch fermentations based on frequency content analysis

A new strategy for controlling substrate feed in the exponential growth phase of aerated fed‐batch fermentations is presented. The challenge in this phase is typically to maximize specific growth rate while avoiding the accumulation of overflow metabolites which can occur at high substrate feed rates. In the new strategy, regular perturbations to the feed rate are applied and the proximity to overflow metabolism is continuously assessed from the frequency spectrum of the dissolved oxygen signal. The power spectral density for the frequency of the external perturbations is used as a control variable in a controller to regulate the substrate feed. The strategy was implemented in an industrial pilot scale fermentation set up and calibrated and verified using an amylase producing Bacillus licheniformis strain. It was shown that a higher biomass yield could be obtained without excessive accumulation of harmful overflow metabolites. The general applicability of the strategy was further demonstrated by implementing the controller in another process using a Bacillus licheniformis strain currently used in industrial production processes. In addition, in this case a higher growth rate and decreased accumulation of overflow metabolites in the exponential growth phase was achieved in comparison to the reference controller. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:817–824, 2013     

Cell-mass maximization in fed-batch cultures

Complete solutions are provided for cell-mass maximization for free and fixed final times and constant and variable yields. The optimal feed rate profile is a concatenation of maximum, minimum and singular feed rates. The exact sequence and duration of each feed rate depends primarily on the initial substrate concentration, and degenerate cases arise due to the magnitude constraint on the feed rate and the length of final time t _f. When the final time is free and not in the performance index, it is infinite for constant yield so that any form of feed rate leads to the same amount of cells, while for variable yield the singular feed rate is exponential and maximizes the yield. For fixed final time the singular feed rate for constant yield is exponential and maximizes the specific growth rate by maintaining the substrate concentration constant, while for variable yield, it is semi-exponential and the substrate concentration starts near the maximum specific growth rate and moves toward the maximum yield. A simple sufficient condition for existence of singular feed rate requires an existence of a region bounded by the maxima of specific growth and cellular yield. Otherwise, the optimal feed rate profile is a bang-bang type and the bioreactor operates in batch mode.     

Feedback stabilization of fed-batch bioreactors: non-monotonic growth kinetics

This paper deals with the design of a feedback controller for fed-batch microbial conversion processes that forces the substrate concentration C(S) to a desired setpoint, starting from an arbitrary (initial) substrate concentration when non-monotonic growth kinetics apply. This problem is representative for a lot of industrial fermentation processes, with the baker's yeast fermentation as a well-known example. It is assumed that the specific growth rate mu is function of the substrate concentration only. A first approach exploits the availability of on-line measurements of both the substrate and biomass concentration. A second approach is merely based on on-line measurements of the biomass concentration, which provide an estimate for the specific growth rate. After a reformulation of the substrate concentration setpoint into a specific growth rate setpoint, it is demonstrated that the fed-batch process can still be stabilized around any desired operating point along the non-monotonic kinetics.     

Comparative evaluation of various control schemes for fed-batch fermentation

The crucial problem associated with control of fed-batch fermentation process is its time-varying characteristics. A successful controller should be able to deal with this feature in addition to the inherent nonlinear characteristics of the process. In this work, various schemes for controlling the glucose feed rate of fed-batch baker's yeast fermentation were evaluated. The controllers evaluated are fixed-gain proportional-integral (PI), scheduled-gain PI, adaptive neural network and hybrid neural network PI. The difference between the specific carbon dioxide evolution rate and oxygen uptake rate (Q_c-Q_o) was used as the controller variable. The evaluation was carried out by observing the performance of the controllers in dealing with setpoint tracking and disturbance rejection. The results confirm the unsatisfactory performance of the conventional controller where significant oscillation and offsets exist. Among the controllers considered, the hybrid neural network PI controller shows good performance.     

Nonlinear feedforward control of bioreactors with input multiplicities

A steady-state nonlinear feedforward controller (FFC) for measurable disturbances is designed for a continuous bioreactor, which is represented by Hammerstein type nonlinear model wherein the nonlinearity is a polynomial with input multiplicities. The manipulated variable is the feed substrate concentration (S_f) and the disturbance variable is the dilution rate (D). The productivity (Q=DP) is considered as the controlled variable. The desired value of Q=3.73 gives two values of feed substrate concentration. The nonlinearity in the gain is considered for relating output to the manipulated variable and separately for the relation between output to disturbance variable. The FFC is also designed for the overall linearized system. The performance of the FFC is evaluated on the nonlinear differential equation model. The FFC is also designed for the model based on a single nonlinear steady-state equation containing both D and S_f. This nonlinear FFC gives the best performance. The nonlinear FFC is also designed by using only linear gain for the disturbance and nonlinear gain for the manipulated variable. Similarly, nonlinear FFC is also designed by using linear gain for the manipulated variable and the nonlinear gain for the disturbance variable. The performances of these FFC schemes are compared.     

Secretion-dependent proteolysis of heterologous protein by recombinant Escherichia coli is connected to an increased activity of the energy-generating dissimilatory pathway

The synthesis of a proteolytically unstable protein, originally designed for periplasmic export in recombinant Escherichia coli BL21(DE3), a strain naturally deficient for the ATP-dependent protease Lon (or La) and the outer membrane protease OmpT, is associated with a severe growth inhibition. This inhibition is not observed in BL21(DE3) synthesizing a closely related but proteolytically stable protein that is sequestered into inclusion bodies. It is shown that the growth inhibition is mainly caused by a slower cell division rate and a reduced growth yield and not by a general loss of cell division competence. Cells proceed with their normal growth characteristics when exposed again to conditions that do not sustain the expression of the heterologous gene. The performance of cells synthesizing either the stable or the degraded protein was also studied in high cell density cultures by employing a new method to calculate the actual specific growth rate, the biomass yield coefficient, and the dissimilated fraction of the carbon substrate in real-time. It is shown that the growth inhibition of cells synthesizing the proteolytically degraded protein is connected to an increased dissimilation of the carbon substrate resulting in a concomitant reduction of the growth rate and the biomass yield coefficient with respect to the carbon source. It is postulated that the increased dissimilation of the carbon substrate by lon-deficient Bl21(DE3) cells synthesizing the proteolytically unstable protein may result from a higher energy demand required for the in vivo degradation of this protein by ATP-dependent proteases different from the protease Lon.     

Unstable steady state operations of substrate inhibited cultures by dissolved oxygen control

Microorganism kinetic growth characterized by substrate inhibition was investigated by means of a continuous stirred tank reactor equipped with a feedback controller of the medium feeding flow rate. The aerobic growth of Pseudomonas sp. OX1 with phenol as carbon/energy source was adopted as a case study to test a new control strategy using dissolved oxygen concentration as a state variable. The controller was successful in steadily operating bioconversion under intrinsically unstable conditions. A simple model of the controlled system was proposed to set the feedback controller.The specific growth rate of Pseudomonas sp. OX1 was successfully described by means of the Haldane model. The regression of the experimental data yielded μ_M = 0.26 h⁻¹, K_Ph = 5 × 10⁻³ g/L and K_I = 0.2 g/L. The biomass-to-substrate fractional yield as a function of the specific growth rate did not change moving from substrate-inhibited to substrate-deficient state. The data was modelled according to the Pirt model: m = 1.7 × 10⁻² g/(g h), . The specific growth rates calculated for batch and continuous growth were compared.     

Control of unstable bioreactor using fuzzy tuned PI controller

A fuzzy tuning scheme for conventional PI controller is developed for controlling an unstable continuous bioreactor. The performance is compared with that of a fixed setting conventional PI controller. The performance of the tuning scheme is studied by simulating the non-linear model equations of the bioreactor. The robustness of the controller is also studied for uncertainties in the process parameters such as yield factor and measurement delay. Simulation results show that the fuzzy tuning improves the overall performance and particularly it is more robust to parameter uncertainties.