动态MPCA在发酵过程监测与故障诊断中的应用

针对发酵过程非线性和时变特点,提出了一种具有实时性的动态MPCA方法,采用多模型非线性结构代替传统MPCA单模型线性化结构,克服了后者不能处理非线性过程和实时性的问题,并避免了MPCA在线应用时预报未来测量值带来的误差,提高了发酵过程性能监测和故障诊断的准确性。对头孢菌素C发酵过程的拟在线仿真研究,验证了基于动态MPCA的统计过程监测的有效性。     

α-Amylase,Limit Dextrinase,and α-Glucosidase Enzymes in Barley and Malt

Abstract

A parallel discussion is presented of recent developments in fermentation monitoring and control in both research institutes and in industry. The discussion is based around the areas of measurement (on-line and off-line), data conditioning and analysis, modeling, fault analysis, and control. Recent progress in industrial fermentation monitoring and control is used as a guide to identify potential areas of research that might have a most rapid and direct impact on industrial fermentation operation.     

On-line analysis of avermectin fermentation cell growth kinetics in an industrial pilot plant

Experimental data are presented which show that on-line calculation of oxygen uptake rate can be used to estimate the cell concentration of Streptomyces avermitilis during the active growth phase of this fermentation. Moreover, by dividing the oxygen uptake rate by the total oxygen consumed, an on-line estimate of specific growth rate of this culture can be generated. A theoretical basis is provided for this model. Use of a mass spectrometer for vent gas analysis coupled with computer data acquisition has made this information both very accurate and readily available. Examples are given which illustrate the kinetics of the avermectin fermentation as well as the effect of a temperature shift on the specific growth rate.     

On-line process monitoring and chemometric modeling with 2D fluorescence spectra obtained in recombinant E. coli fermentations

2D spectrofluorometry produces a large volume of spectral data during fermentation processes with recombinant E. coli, which can be analyzed using chemometric methods such as principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS). An analysis of the spectral data by PCA results in scores and loadings that are not only visualized in the score-loading plots but are also used to monitor the fermentation processes on-line. The score plots provided useful qualitative information on four fermentation processes for the production of extracellular 5-aminolevulinic acid (ALA). Two chemometric models (PCR and PLS) were used to examine the correlation between the 2D fluorescence spectra and a few parameters of the fermentation processes. The results showed that PLS had slightly better calibration and prediction performance than PCR.     

Reconfigurable control system design for fault diagnosis and accommodation

The growing demand in system reliability and survivability under failures has urged ever-increasing research effort on the development of fault diagnosis and accommodation. In this paper, the on-line fault tolerant control problem for dynamic systems under unanticipated failures is investigated from a realistic point of view without any specific assumption on the type of system dynamical structure or failure scenarios. The sufficient conditions for system on-line stability under catastrophic failures have been derived using the discrete-time Lyapunov stability theory. Based upon the existing control theory and the modern computational intelligence techniques, an on-line fault accommodation control strategy is proposed to deal with the desired trajectory-tracking problems for systems suffering from various unknown and unanticipated catastrophic component failures. Theoretical analysis indicates that the control problem of interest can be solved on-line without a complete realization of the unknown failure dynamics provided an on-line estimator satisfies certain conditions. Through the on-line estimator, effective control signals to accommodate the dynamic failures can be computed using only the partially available information of the faults. Several on-line simulation studies have been presented to demonstrate the effectiveness of the proposed strategy. To investigate the feasibility of using the developed technique for unanticipated fault accommodation in hardware under the real-time environment, an on-line fault tolerant control test bed has been constructed to validate the proposed technology. Both on-line simulations and the real-time experiment show encouraging results and promising futures of on-line real-time fault tolerant control based solely upon insufficient information of the system dynamics and the failure dynamics.     

An on-line approach to monitor ethanol fermentation using FTIR spectroscopy

Fermentation process control is currently limited by its inability to measure parameters such as substrate, product, and biomass concentrations rapidly for consistent on-line feedback. Physical and chemical parameters, such as temperature and pH, currently can be obtained on-line using appropriate sensors. However, to obtain information on the concentration of the substrate, product, and biomass, samples must be taken off-line for measurement. With the use of spectroscopic techniques, real-time monitoring of process constituents such as product and substrate is possible. Spectroscopic techniques are rapid and nondestructive, require minimal or no sample preparation, and can be used to simultaneously assess several constituents in complex matrices. The production of ethanol is the largest fermentation process in terms of production volume and economic value as a result of its prominence in the food, agricultural, and fuel industries. This study attempts to develop an on-line ethanol fermentation monitoring technique using Fourier transform infrared (FTIR) spectroscopy with a flow-through ATR capability. Models developed using multivariate statistics, employed to obtain on-line FTIR measurements, were successfully validated by off-line HPLC analysis and spectrophotometry data. Standard errors of prediction (SEP) values of 0.985 g/L (R2 = 0.996), 1.386 g/L (R2 = 0.998), and 0.546 (R2 = 0.972) were obtained for ethanol, glucose, and OD, respectively. This work demonstrates that FTIR spectroscopy could be used for rapid on-line monitoring of fermentation.     

Gas chromatography and gateway sensors for on-line state estimation of complex fermentations (butanol-acetone fermentation)

A fermentation system has been designed to demonstrate the use of gas chromatography (GC) for on-line monitoring of the butanol-acetone and other complex saccharolytic fermentations. Tangential flow ultrafiltration was used to sterilely and continuously obtain a cell-free filtrate from the fermentation broth for on-line GC analysis of butanol, butyrate, acetate, acetone, ethanol, and acetoin. The liquid injection system consists of a phosphoric acid contactor, a slider-type injection valve, and a heater to address the difficulties (ghosting) encountered in the analysis of carboxylic acids. The fermentation headspace gas was also analyzed by on-line GC for nitrogen and carbon dioxide, while hydrogen was measured by difference. Raw chromatographic data were analyzed by a chromatography data system. Both raw and processed data were transmitted to a VAX 11/750 computer for further processing (using the fermentation equation) and archiving. The fermentation equation, which has recently been derived and tested on completed fermentation data, was also found to be valid during transient fermentations and thus useful as a gateway sensor for calculating various fermentation parameters on-line. Such parameters include glucose concentration and gas composition, as well as a number of unobservable parameters (such as Y(ATP), excess ATP, and NAD reduced by FdH(2)), which characterize the state of the fermentation.     

Adaptive on-line simulation of bioreactors: Fermentation monitoring and modeling system

Summary In order to study and control fermentation processes, indirect on-line measurements and mathematical models can be used. Here an on-line model for fermentation processes is presented. The model is based on atom and partial mass balances as well as on stability equations for the protolytes. The model is given an adaptive form by including transport equations for mass transfer and expressions for the fermentation kinetics. The state of the process can be estimated on-line using the balance component of the model completed with measurement equations for the input and the output flows of the process. Adaptivity is realized by means of on-line estimation of the parameters in the transport and kinetic expressions using recursive regression analysis. On-line estimation of the kinetic and mass transfer parameters makes model-based predictions possible and enables intelligent process control while facilitating testing of the validity of the measurement variables. A practical MS-Windows 3.1 model implementation called FMMS—Fermentation Monitoring and Modeling System is shown. The system makes it easy to configure the operating conditions for a run. It uses Windows dialogs for all set-ups, model configuration parameters, elemental compositions, on-line measurement devices and signal conditioning. Advanced on-line data analysis makes it possible to plot variables against each other for easy comparison. FMMS keeps track of over 100 variables per run. These variables are either measured or estimated by the model. Assay results can also be entered and plotted during fermentation. Thus the model can be verified almost instantly. Historical fermentation runs can be re-analyzed in simulation mode. This makes it possible to examine different signal conditining filters as well as the sensitivity of the model. Combined, the data analysis and the simulation mode make it easy to test and develop model theories and new ideas.     

Computer-aided baker's yeast fermentations.

The economics of yeast production depend heavily upon the cellular yield coefficient on the carbon source and the volumetric productivity of the process. The application of an on-line computer to maximize these two terms during the fermentation requires a continuous method of measuring cell density and growth rate. Unfortunately, a direct sensor for biomass concentration suitable for use in industrial fermentations is not available. Material balancing, with the aid of on-line computer monitoring, offers an indirect method of measurement. Laboratory results from baker's yeast production in a 14-liter fermentor (with a PDP-11/10 computer for on-line analyses) show this indirect measurement technique to be a viable alternative. From the oxygen uptake and carbon dioxide production data, gas flow rate, and ammonia addition rate, the cell density during the fermentation has been estimated and found to compare well with actual fermentation data.     

Neural network predictive control by MIMS monitored 2,3-butanediol fermentation by Klebsiella oxytoca

With the aid of a membrane introduction mass spectrometer (MIMS), the major product 2,3-butanediol (2,3-BDL) as well as the other metabolites from the fermentation carried by Klebsiella oxytoca can be measured on-line simultaneously. A backpropagation neural network (BPN) being recognized with superior mapping ability was applied to this control study. This neural network adaptive control differs from those conventional controls for fermentation systems in which the measurements of cell mass and glucose are not included in the network model. It is only the measured product concentrations from the MIMS that are involved. Oxygen composition was chosen to be the control variable for this fermentation system. Oxygen composition was directly correlated to the measured product concentrations in the controller model. A two-dimensional (number of input nodes by number of data sets) moving window for on-line, dynamic learning of this fermentation system was applied. The input nodes of the network were also properly selected. Number of the training data sets for obtaining better control results was also determined empirically. Two control structures for this 2,3-BDL fermentation are discussed and compared in this work. The effect from adding time delay element to the network controller was also investigated.     

Experimental adaptive on-line optimization of cellular productivity of a continuous bakers' yeast culture

An adaptive on-line optimization method that utilizes dynamic model identification has been applied to maximize the cellular productivity of a continuous bakers' yeast culture. Experiments were conducted on a sophisticated computerized fermentation system. Experimental results show that the adaptive on-line optimization method requires very little a priori information, is easy to implement, converges quickly, adapts to changes in the process, and is stable even when operational difficulties are encountered.     

A database system for fermentation processes

Data base management is needed in the whole industries, particularly in the fermentation industry, whose jobs are tedious yet require carefulness. The most important problem in the database system is not how to collect many informations, but how to handle the meaningful ones.The authors have recently developed an on-line monitoring and control system for the fermentation processes in co-operation with Fuji Facom Co. Ltd. and Komatsugawa Chemical Engineering Co. Ltd.This system enables us to measure directly those concentrations in fermentation systems which have been measured by offline so far, such as cell mass, substrate and metabolic products. The physiological activities of a microorganism, such as specific rate of cellular growth, that of substrate consumption, that of metabolites production, etc., became estimable precisely by eliminating the effect of noises.By enlarging the function of our monitoring and control system, we have developed a database system which is applicable in job scheduling not only in the laboratory but also in the production line, in automatic resource allocation and fault analyses of the fermentation processes.     

An algorithm for operating a fed-batch fermentor at optimum specific-growth rate

An algorithm for operating a fed-batch fermentor at an optimum specific fermentation rate is proposed. It does not require on-line measurement of nutrient concentration in the culture medium. An on-line estimate of the specific fermentation rate is sufficient for implementation of this scheme. The algorithm is model independent and works well even with poor estimates of the product yields and the specific fermentation rate. Results of a detailed simulation study are presented for a simple case of optimization of cell-mass production in a fed-batch fermentor. The results clearly demonstrate the efficacy of this algorithm under a wide range of fermentation situations.     

Use of an Extended Kalman Filter and development of an automated system for xylose fermentation by a recombinantEscherichia coli

Summary An automated system was developed for on-line monitoring and control of xylose fermentation by a recombinantEscherichia coli. A 7-L fermenter was interfaced with a personal computer. Control circuits were constructed and a software was developed to estimate the states of the fermentation using an Extended Kalman Filter. The automated system combined with the Extended Kalman Filter provided a satisfactory way to obtain on-line information regarding estimation of fermentation parameters.     

Monitoring of recombinant protein production using bioluminescence in a semiautomated fermentation process

On-line optimization of fermentation processes can be greatly aided by the availability of information on the physiological state of the cell. The goal of our "BioLux" research project was to design a recombinant cell capable of intracellular monitoring of product synthesis and to use it as part of an automated fermentation system. A recombinant plasmid was constructed containing an inducible promoter that controls the gene coding for a model protein and the genes necessary for bioluminescence. The cells were cultured in microfermenters equipped with an on-line turbidity sensor and a specially designed on-line light sensor capable of continuous measurement of bioluminescence. Initial studies were done under simple culture conditions, and a linear correlation between luminescence and protein production was obtained. Such specially designed recombinant bioluminescent cells can potentially be applied for model-based inference of intracellular product formation, as well as for optimization and control of recombinant fermentation processes.     

Experimental studies of network parameters and operational variables on recurrent backpropagation neural network adaptive control of penicillin acylase fermentation by Arthrobacter viscosus

This work is to investigate the on-line control of the fermentation by Arthrobacter viscosus. This species of bacteria can secrete penicillin acylase which is a key enzyme in pharmaceutical industry. The growth of more cells during the fermentation will obtain more enzyme. Both the enzyme activity and the cell growth are rather sensitive to the change of pH. Once the pH during a fermentation is not properly controlled, the decay of cells' activity will irreversibly occur. Two peristaltic pumps for supplying acidic and basic solutions, respectively, were connected for the regulation of pH. With superior ability in identification and prediction of dynamic time series, recurrent backpropagation network (RBPN), instead of conventional controllers, was used as the adaptive controller model for the fermentation with dynamic characteristics. Based on a 1-3-1 BPN, a corresponding 4-4-1 RBPN was determined. The deviation of the pH measured at current time from the set point of 7.0, denoted as ( pH(t), was chosen as the input node of the network controller. The output node of this network controller was the predicted flow rate of the peristaltic pump for next control time interval. Such a model was operated by two phases. During the first phase, the network was set as the process model and trained by a fixed set of on-line acquired data. During the second phase, the network was stopped learning and switched to become a predictor, the predicted control action was hence obtained. The optimum sampling time was determined experimentally. To enhance the effective computation of this network, the number of training data was limited. A moving-window type of supplying training data to the network was applied for the on-line learning. The window size was also determined for each learning. With properly chosen network parameters as well as operation conditions, pH of the fermentation was thus well controlled by the RBPN controller.     

Enhanced production of L-(+)-lactic acid in chemostat by Lactobacillus casei DSM 20011 using ion-exchange resins and cross-flow filtration in a fully automated pilot plant controlled via NIR

Due to the lack of suitable in-process sensors, on-line monitoring of fermentation processes is restricted almost exclusively to the measurement of physical parameters only indirectly related to key process variables, i.e., substrate, product, and biomass concentration. This obstacle can be overcome by near infrared (NIR) spectroscopy, which allows not only real-time process monitoring, but also automated process control, provided that NIR-generated information is fed to a suitable computerized bioreactor control system. Once the relevant calibrations have been obtained, substrate, biomass and product concentration can be evaluated on-line and used by the bioreactor control system to manage the fermentation. In this work, an NIR-based control system allowed the full automation of a small-scale pilot plant for lactic acid production and provided an excellent tool for process optimization. The growth-inhibiting effect of lactic acid present in the culture broth is enhanced when the growth-limiting substrate, glucose, is also present at relatively high concentrations. Both combined factors can result in a severe reduction of the performance of the lactate production process. A dedicated software enabling on-line NIR data acquisition and reduction, and automated process management through feed addition, culture removal and/or product recovery by microfiltration was developed in order to allow the implementation of continuous fermentation processes with recycling of culture medium and cell recycling. Both operation modes were tested at different dilution rates and the respective cultivation parameters observed were compared with those obtained in a conventional continuous fermentation. Steady states were obtained in both modes with high performance on lactate production. The highest lactate volumetric productivity, 138 g L(-1) h(-1), was obtained in continuous fermentation with cell recycling.     

Adaptive on-line model for aerobic Saccharomyces cerevisiae fermentation

In order to study and control fermentation processes, indirect on-tine measurements and mathematical models can be used. In this article we present a mathematical on-line model for fermentation processes. The model is based on atom and partial mass balances as well as on equations describing the acid-base system. The model is brought into an adaptive form by including transport equations for mass transfer and unstructured expressions for the fermentation kinetics. The state of the process, i.e., the concentrations of biomass, substrate, and products, can be estimated on-line using the balance part of the model completed with measurement equations for the input and output flows of the process. Adaptivity is realized by means of on-line estimation of parameters in the transport and kinetic expressions using recursive regression analysis. These expressions can thus be used in the model as valid equations enabling prediction of the process. This makes model-based automation of the process and testing of the validity of the measurement variables possible. The model and the on-line principles are applied to a 3.5-L laboratory tormentor in which Saccharomyces cerevisiae is cultivated. The experimental results show that the model-based estimation of the state and the predictions of the process correlate closely with high-performance liquid chromatography (HPLC) analyses. (c) 1995 John Wiley & Sons, Inc.     

On-line monitoring of lipase production in fermentation processes

Summary The results obtained in on-line monitoring of lipase production byCandida rugosa in a batch fermentation process are presented. For this purpose an automatic lipase concentration analyzer has been developed and tested. Its good reproducibility and its capability to perform the analysis in less time than the classical titrimetric method make it very suitable for on-line determination lipase concentration in fermentation processes.