Fermentation Processes Monitoring and Control Using Generalized Nets

Transcription

1 Годишник на секция Информатика Съюз на учените в България Том 2, 2009, Annua of Informatics Section Union of Scientists in Bugaria Voume 2, 2009, Fermentation Processes Monitoring and Contro Using Generaized Nets Oympia Roeva, Stoyan Tzonkov Centre of Biomedica Engineering, Bugarian Academy of Sciences 105, Acad. G. Bonchev Str., Sofia 1113, Bugaria Abstract: In this paper a generaized net mode for monitoring and contro of main of physics-chemica parameters, gases, as we as foam eves of fermentation processes is deveoped. Generaized nets are preiminary proved to be an appropriate too for description of the ogics of fermentation process modeing, incuding the opportunity for the biochemica variabes of considered processes to be described. The proposed generaized net mode for monitoring and contro of fermentation processes is a combination of aready deveoped generaized nets into a singe mode, that aows optima process impementation through monitoring and contro of essentia process variabes and parameters. Keywords: Generaized nets, Monitoring and contro, Fermentation processes. 1. Introduction Considering fermentation processes, a bioreactors used nowadays use contro strategies for three basic environmenta factors: ph, temperature and dissoved oxygen (DO). Invariaby, these contro impementations are achieved via reguation of fow rate of acid/base, fow rate of fuid through the cooing coi, and agitation, respectivey. Needess to say, these three parameters are extremey important for optima ceuar activity. But they aone do not guarantee the maximum productivity, which is the objective for most of the industria fermentations. A contro system cannot be impemented uness the process under consideration has been understood. An efficient way of understanding the process is constructing a mathematica mode. A good process mode is an invauabe too to deveop a contro agorithm. It is not impied that controers are unabe to contro poory understood processes; in practice, this is how they often function. However, an expensive, and timeconsuming tria and error adjustment of the contro agorithm is required in that case. Automatic contro systems have advanced far from their initia appications in the process industries. The conversion from oca singe-input singe-output oops through initia appication of advanced methods to current mutivariabe, adaptive, and neura network appications has increased pant profits. The use of Generaized Nets (GNs) [1-3] affords the opportunities for on-ine contro; searching of optima process conditions; earning on the basis of experimenta data; contro on the basis of expert systems, etc. The 38

2 faciity of obtaining GN modes demonstrates the fexibiity and the efficiency of generaized nets as modeing toos in different fieds [1-3, 12]. This fact provokes the idea of deveoping a GN mode for fermentation processes monitoring and contro. So far, GNs have been used as a too for modeing of various operationa modes of fermentation processes, for different processes such as fed-batch fermentation of E. coi and Br. favu, as we as for wastewater treatment processes, [12]. On the other hand, generaized nets are used for optima contro of fermentation processes [4], PID controer [11], and for monitoring and contro of some physics-chemica parameters of considered processes, such as temperature [7, 9], ph [8], DO [6], carbon dioxide (CO 2 ) [10] and foam eves [5]. The known advantages of the generaized nets presents them as a very appropriate too for the modeing compex processes such as fermentation processes. The generaized nets modes, that have been deveoped so far, aow us to simuate the fermentation processes easiy and quicky [12]. This paper is focused on the appication of these aready deveoped generaized nets for the fermentation processes monitoring and contro. In this work a GN mode is proposed that generaizes the known GNs for monitoring and contro of physics-chemica parameters, gases and foam eve of considered processes. 2. Monitoring and Contro of Fermentation Processes The proposed generaized net mode describes a system for monitoring and contro of physics-chemica parameters (ph, temperature), gases (DO and CO 2 ) and foam during a fed-batch fermentation process [13, 14]. An exampe of fermentation processes monitoring and contro is presented on Figure 1. Parameters that must be precisey reguated are: temperature, ph and oxygenation (DO). In addition, monitoring and contro of the CO 2 and foam eve is needed [13, 14]. Monitoring and temperature contro Temperature is one of the most infuentia factors affecting the fermentation process. Temperature affects the growth and activity of a iving ces. At high temperatures, organisms are destroyed, whie at ow temperatures their rate of activity is decreased or even suspended. A generaized net mode describing the whoe system for temperature contro in the bioreactor is deveoped [7]. The GN mode permits to contro the temperature at a desired vaue during the fermentation processes. The apparatus of generaized nets aows easy and simpe in ogics description of temperature contro system. The GN mode aows taking into account factors that affect the temperature contro system, and it presents the cacuation of water temperature that shoud be added into the doube jacket of the bioreactor. This ensures the contro of the temperature at the desired vaue during the fermentation processes. 39

3 Figure 1. Fermentation processes monitoring and contro 40

4 Monitoring and ph contro Contro and monitoring of ph is an important aspect of many industria biotechnoogica processes in order to provide the optima conditions for microorganisms growth. ph is one of the most important chemica environmenta measurements used to indicate the course of the biotechnoogica process. It detects the presence of specific chemica factors that infuence growth, metaboism, and fina product. A generaized net mode, describing ph contro system, is presented in [8]. The GN mode, taking into account the vaue of ph in the bioreactor, determines which reagent shoud be added to the bioreactor. If the cuture medium is acidic, then a base shoud be infused. Otherwise, if the cuture medium is basic, then an acid shoud be infused. An effective and we controed ph adjustment system wi use as itte reagent as possibe. Monitoring and dissoved oxygen contro The contro of DO in microbia fermentations creates probems on both aboratory and piot/production scae. This is most frequenty due to: The increasing overa oxygen demand with increasing biomass. Changing mass transfer coefficient due to changes of fuid characteristics by metaboic products. Foaming at high aeration rates and high stirrer speed. The contro of oxygen is even more compicated if it is controed by both airfow or oxygen concentration in the aeration gas and stirrer speed. In this case, traditiona contro strategies woud normay empoy proportiona integra differentia (PID) agorithms connected to a contro cascade [13, 14]. As the contro oop is dependent on the overa oxygen consumption, which increases dramaticay with exponentiay proiferating biomass, optima tuning of the controer wi be inked to oxygen uptake rate. In [6], a generaized net mode of oxygen contro system in fermentation processes is presented. The presented generaized net mode describes the operations in the dissoved oxygen contro during the fermentation processes and aows the DO concentration to be kept within the desired interva [DO min, DO max ]. The contro coud be done easiy and in simpe ogic. The GN mode, taking into account the DO concentration in the bioreactor, determines variation of rotation speed of the stirrer or variation of the aeration gas concentration added to the bioreactor. Monitoring and carbon dioxide contro Exhaust gas monitoring is a powerfu too for process contro and troubeshooting at a scaes of fermentation, as fermentation activity is refected in the O 2 consumption and CO 2 production. In conjunction with ph and dissoved oxygen, in-situ measurement of dissoved CO 2 is a critica parameter in evauating the respiratory efficiency of microorganisms in ce cuture. Any deviation from the optima metaboism of the microorganism can be refected in the respiratory quotient. Using the apparatus of GNs, a net mode for monitoring of CO 2 concentration during fermentation processes is proposed in [10]. Appying deveoped GN, optima conditions for microbia growth process can be ensured and current process status based on the observed vaues of CO 2 concentration and RQ can be determined. Ensuring better monitoring and contro of exhaust gases is a precondition for higher efficiency of the fermentation process. 41

5 Monitoring and foam contro Microbia fermentation requires a high amount of agitation and aeration, which often resuts in excessive foaming. Antifoam controers prevent foam eves from getting too high. Excessive foam tends to emerge through ports in the headpate, open the system to contamination, and inhibit proper oxygen transfer. Many investigations show that the contro of the foam eve is important for optima run of the cutivation process [13, 14]. A generaized net mode of the foam monitoring contro system during a cutivation process is deveoped in [5]. The proposed GN mode permits to contro the foam eve in an appropriate vaue. The GN mode, taking into account the foam eve in the bioreactor and decides if a proper amount of defoaming agent shoud be added to the cuture medium or not. 3. Generaized Net Mode The generaized net mode, describing the considered system, is presented in Figure 2. The mode is based on the GN mode for fed-batch operationa mode [12] and generaizes previousy deveoped modes for monitoring and contro of the parameters temperature, ph, DO, CO 2 and foam eves. It is shown that the GN mode deveoped for fed-batch mode can be easiy transformed for batch and continuous mode, [12]. Figure 2. GN mode for fermentation processes monitoring and contro The token α enters GN through pace 1 with an initia characteristic Fow rate of the medium feed. The form of the first transition of the GN mode is: 42

6 2 3 Z 1 = <{ 1, 3 }, { 2, 3 },, ( 1 fase 1, 3 )>, W 3 1 where W 1 is Need of new concentration of substrate, depending on the substrate vaue in pace 6. The token α obtains the characteristics Concentration of the substrate added to the bioreactor in pace 2, Amount of medium feed in storage in pace 3. The token β enters GN in paces 4 with a characteristic Initia concentration of process variabes. As process variabes are considered substrate(s), biomass, product(s) and bioreactor voume. In pace 5 the token γ enters the GN mode with a characteristic Initia concentration of physics-chemica parameters (temperature and ph), gases (DO and CO 2 ) and foam eve. The form of the second transition of the GN mode is: Z 2 = < { 2, 4, 5 }, { 6, 7, 8, 9, 10, 11 }, r 2, ( 2, 4, 5 ) > r 11 2 = 2 W 3 W 3 W 3 W 3 W 3 4 W 4 W 4 W 4 W 4 W 4 5 W 2 W 5 W 5 W 5 W 5 W 5 where W 2 is Presence of parameter vaues (pace 5 ) in the mathematica description of process parameters dynamics ; W 3 is Presence of parameter vaues (pace 2 ) in the mathematica description of temperature and ph, gases (DO and CO 2 ) and foam eve dynamics ; W 4 is Presence of parameter vaues (pace 4 ) in the mathematica description of temperature and ph, gases (DO and CO 2 ) and foam eve dynamics ; W 5 is Presence of parameter vaues (pace 5 ) in the mathematica description of temperature and ph, gases (DO and CO 2 ) and foam eve dynamics. In pace 6 information about tokens α (pace 2 ) and β (pace 4 ) is combined in a new token δ that keeps the information about the concentration of the process variabes (substrate(s), biomass, product(s) and bioreactor voume) in the current moment, i.e. has a characteristic Main process information. The token γ is spit into five tokens (ρ 1, ρ 2, ρ 3, ρ 4 and ρ 5 ) respectivey in paces 7, 8, 9, 10 and 11. Through the hierarchica operator H 1 (see [1]) paces 7, 8, 9, 10 and 11 are substituted with the corresponding GN mode for monitoring and contro as foows: pace 7 is repaced with GN mode for contro of temperature, presented in [7]; pace 8 is repaced with GN mode of ph contro system, presented in [8]; pace 9 is repaced with GN mode of oxygen contro system, presented in [6]; pace 10 is repaced with GN mode for carbon dioxide monitoring, presented in [10]; 43

7 pace 11 is repaced with GN mode of foam monitoring contro systems presented in [5]. The form of the third transition of the GN mode is: Z 3 = <{ 6, 7, 8, 9, 10, 11 }, { 12, 13 }, fase fase fase fase fase 13 fase, ( 6, 7, 8, 9, 10, 11 )>, In pace 12 the token δ keeps its previous characteristic Main process information. In pace 13 the tokens ρ i are combined into one token ρ whit characteristic Information of physics-chemica parameters (temperature and ph), gases (DO and CO 2 ) and foam eve. The form of the fourth transition of the GN mode is: Z 4 = <{ 12, 15 },{ 14, 15 }, 12 fase, ( 12, 15 )>, W W where W 6 is End of the fed-batch cutivation process and W 7 = W 6. The token δ obtains the characteristics Main process information in the end of the process in pace 14 and Main process information during the process in pace 15. The form of the fifth transition of the GN mode is: Z 5 = <{ 13, 17 }, { 16, 17 }, 13 fase, ( 13, 17 ) >. W W The token ρ obtains the foowing characteristics: in pace 16 Information of physics-chemica parameters (temperature and ph), gases (DO and CO 2 ) and foam eve in the end of the process ; in pace 17 Information of physics-chemica parameters (temperature and ph), gases (DO and CO 2 ) and foam eve during the process. The resuting net mode, which is a generaization of aready deveoped GN modes [5-8, 10] gives possibiity for optima process impementation through monitoring and contro of essentia process variabes and parameters. 44

8 References [1] Atanassov K., On Generaized Nets Theory, Prof. Marin Drinov Acad. Pub. House, Sofia, [2] Atanassov K., Generaized Nets and Systems Theory, Sofia, Academic Pubishing House Prof. M. Drinov, [3] Atanassov K., Generaized Nets, Singapore, New Jersey, London, Word Scientific, [4] Roeva O., Generaized Net for Optima Feed Rate Contro of Fed-batch Fermentation Processes, Proceedings of the Fifth Internationa Workshop on Generaized Nets, Sofia, November 10, 2004, [5] Roeva O., Generaized Net Mode for Foam Monitoring Contro Systems, Proceedings of the Eighth Internationa Workshop on Generaized Nets, Sofia, June 26, 2007, [6] Roeva O., Generaized Net Mode of Oxygen Contro System using Intuitionistic Fuzzy Logic, Proceedings of the 1 st Internationa Workshop on Intuitionistic Fuzzy Sets, Generaized Nets and Knowedge Engineering, University of Westminister, London, UK, 6-7 September, 2006, [7] Roeva O., T. Pencheva, Generaized Net for Contro of Temperature in Fermentation Processes, Issues in Intuitionistic Fuzzy Sets and Generaized Nets, Wydawnictwo WSISiZ, Warszawa, 4, 2007, [8] Roeva O., T. Pencheva, Generaized Net Mode of ph Contro System in Biotechnoogica Processes, Proceedings of the Seventh Internationa Workshop on Generaized Nets, Sofia, Juy 14-15, 2006, [9] Roeva O., T. Pencheva, I. Bentes, M. M. Nascimento, Modeing of Temperature Contro System in Fermentation Processes using Generaized Nets and Intuitionistic Fuzzy Logics, Notes on IFS, Proceedings of the Ninth Internationa Conference on Intuitionistic Fuzzy Sets, Sofia, May 7-8, 11(4), 2005, [10] Roeva O., T. Pencheva, St. Tzonkov, Generaized Net for Carbon Dioxide Monitoring of Fermentation, Annua of Informatics Section of Union of Scientists in Bugaria, (Eds. K. Atanassov, V. Boeva, K. Boyanov, S. Denchev, S. Sotirov, M. Todorova), Vo. 1, 2008, ISSN [11] Roeva O., T. Pencheva, St. Tzonkov, Generaized Net for Proportiona-Integra- Derivative Controer, In Book Series Chaenging Probems of Sciences Computer Sciences, 2008, [12] Shannon A., O. Roeva, T. Pencheva, K. Atanassov, Generaized Nets Modeing of Biotechnoogica Processes, Marin Drinov Pubishing House of Bugarian Academy of Sciences, Sofia, 2004, ISBN [13] Tzonkov St., D. Fiev, I. Simeonov, L. Vakev, Contro of Biotechnoogica Processes, Technika, Sofia, [14] Tzonkov St., St. Stoianov, Tz. Georgiev., Basis of Automatic Contro of Biotechnoogica Processes, Technika, Sofia,