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Статті в журналах з теми "PH control system"
van der Schoot, Bart H., Hans Voorthuyzen, and Piet Bergveld. "The pH-static enzyme sensor: Design of the pH control system." Sensors and Actuators B: Chemical 1, no. 1-6 (January 1990): 546–49. http://dx.doi.org/10.1016/0925-4005(90)80270-a.
Повний текст джерелаOoi, W. X., A. W. Hermansson, and C. H. Lim. "Model Predictive Control – Sliding Mode Control of a pH system." IOP Conference Series: Materials Science and Engineering 1257, no. 1 (October 1, 2022): 012036. http://dx.doi.org/10.1088/1757-899x/1257/1/012036.
Повний текст джерелаSafira, M. R., M. W. Lim, and W. S. Chua. "Design of control system for water quality monitoring system for hydroponics application." IOP Conference Series: Materials Science and Engineering 1257, no. 1 (October 1, 2022): 012027. http://dx.doi.org/10.1088/1757-899x/1257/1/012027.
Повний текст джерелаCastanie-Cornet, Marie-Pierre, Thomas A. Penfound, Dean Smith, John F. Elliott, and John W. Foster. "Control of Acid Resistance inEscherichia coli." Journal of Bacteriology 181, no. 11 (June 1, 1999): 3525–35. http://dx.doi.org/10.1128/jb.181.11.3525-3535.1999.
Повний текст джерелаKOBAYASHI, Yusuke, Yuichi NIIBORI, and Tadashi CHIDA. "pH-control by Self-Organizing Fuzzy Controller System." Shigen-to-Sozai 108, no. 1 (1992): 7–12. http://dx.doi.org/10.2473/shigentosozai.108.7.
Повний текст джерелаGrancharova, A., and L. Kostov. "Model Predictive Control of a pH Maintaining System." Information Technologies and Control 11, no. 1 (March 1, 2013): 14–20. http://dx.doi.org/10.2478/itc-2013-0003.
Повний текст джерелаPalancar, María C., José M. Aragón, and José S. Torrecilla. "pH-Control System Based on Artificial Neural Networks." Industrial & Engineering Chemistry Research 37, no. 7 (July 1998): 2729–40. http://dx.doi.org/10.1021/ie970718w.
Повний текст джерелаAgustian, Indra, Bagus Imam Prayoga, Hendy Santosa, Novalio Daratha, and Ruvita Faurina. "NFT Hydroponic Control Using Mamdani Fuzzy Inference System." Journal of Robotics and Control (JRC) 3, no. 3 (May 1, 2022): 374–85. http://dx.doi.org/10.18196/jrc.v3i3.14714.
Повний текст джерелаQian, Yun, Tao Wu, and Meng Fan Zhang. "Design and Implementation of Chemical Wastewater pH Control System." Applied Mechanics and Materials 700 (December 2014): 447–50. http://dx.doi.org/10.4028/www.scientific.net/amm.700.447.
Повний текст джерелаKlimenok, V. I., and O. S. Taramin. "A two-phase GI/PH/1 → ·/PH/1/0 system with losses." Automation and Remote Control 72, no. 5 (May 2011): 1004–16. http://dx.doi.org/10.1134/s0005117911050080.
Повний текст джерелаДисертації з теми "PH control system"
Favaro, Juliana. "Controle preditivo aplicado à planta piloto de neutralização de pH." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-16072013-170810/.
Повний текст джерелаThe predictive control is an advanced control technique which has gained evidence in the economic and ecological context because the search for sustainability and process optimization. This control has already been applied by the chemical and petrochemical industries. The purpose of this project is to develop a predictive controller which will be applied in a pH neutralization plant located in the Industrial Processes Control Laboratory at Polytechnic School of the University of São Paulo. The development of this project can be divided into four stages: implementation of regulatory control loops, identification of the system, construction of the predictive controller, applications and experimental analysis. The first step is necessary in order to study the plant and to implement some internal loops using PID controllers. In the second step, the identification process of the plant model will be done. It is important to note that operating points and internal parameter settings are very important for modeling. In the third stage, using the model obtained from the identification process, a predictive controller is built from auxiliary software such as MATLAB and IIT 800xA (by ABB), which will be used for the development and implementation of the control algorithm. Finally, the last step consists in collecting and analyzing the results of the pH neutralization plant. At this stage the responses of each controller will be compared: PID controller, MPC controller in cascade mode with PID and MPC controller acting directly on actuators.
Alvarado, Christiam Segundo Morales. "Identificação e controle preditivo de uma planta-piloto de neutralização de pH." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-11072014-111203/.
Повний текст джерелаIdentification for control system is based specifically on the mathematical models construction from experimental data, whose aim is to find a relationship between a set of inputs and outputs of a dynamic process. These models are fundamentally important for the industrial processes controllers design. In this work is performed the identification and development of the control system for a pH neutralization pilot plant. The identification procedure is based on the real data collected from pH neutralization process, operating in closed loop. The models estimation is performed in two forms: (1) estimating models that represent all system behavior, including process PID controllers and (2) estimating process models with collecting data of the control signals and process output variables. The process models parameters estimation is performed with the algorithms studied in Chapter 4. With the estimated process models is a MPC (Model Predictive Control) control strategy was designed, creating two control schemes. First scheme will compute the optimal set points that will enter to the process-loops. The second scheme will compute the optimal control signals that will enter to the process. The type of MPC controller adopted is a QDMC (Quadratic Dynamic Matrix Control), allowing restriction of the input and output signals. The control schemes evaluation is performed by changing the set point of the process-loops and the disturbance influence. This disturbance is based on acid flow increased that enters the reactor.
Obut, Salih. "Control Of Ph In Neutralization Reactor Of A Waste Water Treatment System Using Identification Reactor." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/2/12606395/index.pdf.
Повний текст джерелаlinear and has time&ndash
varying characteristics. Therefore, the control of pH is a challenging problem where advanced control strategies are often considered. In this study, the aim is to design a pH control system that will be capable of controlling the pH-value of a plant waste-water effluent stream having unknown acids with unknown concentrations using an on&ndash
line identification procedure. A Model Predictive Controller, MPC, and a Fuzzy Logic Controller, FLC, are designed and used in a laboratory scale pH neutralization system. The characteristic of the upstream flow is obtained by a small identification reactor which has ten times faster dynamics and which is working parallel to actual neutralization tank. In the control strategy, steady&ndash
state titration curve of the process stream is obtained using the data collected in terms of pH value from the response of the identification reactor to a pulse input in base flow rate and using the simulated response of the identification reactor for the same input. After obtaining the steady&ndash
state titration curve, it is used in the design of a Proportional&ndash
Integral, PI, and of an Adaptive Model Predictive Controller, AMPC. On the other hand, identification reactor is not used in the FLC scheme. The performances of the designed controllers are tested mainly for disturbance rejection, set&ndash
point tracking and robustness issues theoretically and experimentally. The superiority of the FLC is verified.
David, William Whalley. "Intracellular pH and Na+ in heart cells during exposure to anisosmolar solutions : regulation of Na+-H+ exchange and Na+-K+ pump activity." Thesis, The University of Sydney, 1992. https://hdl.handle.net/2123/26486.
Повний текст джерелаGuner, Evren. "Adaptive Neuro Fuzzy Inference System Applications In Chemical Processes." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1252246/index.pdf.
Повний текст джерелаTammia, Rasmus. "Modeling and Control of Lime Addition in a Flotation Process." Thesis, Linköpings universitet, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139331.
Повний текст джерелаBoshoff, Gerhardus Marthinus. "Investigating a novel in vitro embryo culture system – The Walking Egg Affordable Assisted Reproductive Technology." Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/63049.
Повний текст джерелаDissertation (MSc)--University of Pretoria, 2017.
Obstetrics and Gynaecology
MSc
Unrestricted
Larsson, Jonathan. "PH-MÄTNING I PAPPERSPRODUKTION : En studie i optimeringar av elektriska mätsystem." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184577.
Повний текст джерелаThe fundamental principle for manufacturing paper is not a complicated one. However, for the paper to acquire specific properties, the process becomes increasingly complicated.Among other things, different chemicals are added, and the process is continuouslymonitored by various systems. One of these systems measures the pH-level of the pulp. This system is however constantly affected by measuring errors, which in turn leads to the incorrect dosage of the carbon dioxide used to lower the pH-level. This could in turn have a negative impact on the properties of the final paper. The underlaying purpose of this project is for the measuring system to ensure an even regulation of pH and therethrough guarantee an even paper quality. For this project, several question at issue, goals and subgoals have been established. The general goals cover establishing a statistical model for the error and estimate possible economical savings. To fulfil the goals and answer the questions at issue, firstly a basic understanding must be established for: concerned parts of the manufacturing process, the effect pH-level has on the process, the measuring principle of the pH-sensor, the design of the measuring systemand the routines concerning the measuring system. With this basis, the occurrence of measuring error is examined for the six measuring points. This is accomplished with two methods: The compilation of historical data and the compilation of manual measurementsexecuted under controlled conditions. The aspects examined are magnitude, frequency and the relation to process related values. Finally, a calculation for costs regarding the measuring system was established. This includes current carbon dioxide and maintenance costs. The result presents a statistical model for the measuring error, divided into historical and near time. The historical model shows that for all the addressed positions, a mean deviation occurred <0.3 pH-units. However, the minimum and maximum deviation could reach >0.8 pH-units. The model for near time shows significant deviations for four out of the six covered positions, which in turn shows relations to both paper quality and surface weight. With this statistical model possible savings were calculated. This in turn showed the possibility of savings for both carbon dioxide and maintenance. The conclusion for this project is the existence of a measuring error. Also, a connection between this and the process related aspects could be established. Although, the result cannot be completely guarantied. With this, possible savings through better accuracy could be estimated. Though, these were only in the size of 0.075‰ of the company’s total revenue.
Alvarado, Christiam Segundo Morales. "Estudo e implementação de métodos de validação de modelos matemáticos aplicados no desenvolvimento de sistemas de controle de processos industriais." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-05092017-092437/.
Повний текст джерелаLinear model validation is the most important stage in System Identification Project because, the model correct selection to represent the most of process dynamic allows the success in the development of predictive and robust controllers, within identification technique finite number and around the operation point. For this reason, the development of linear model validation methods is the main objective in this Thesis, taking as a tools of assessing the statistical, dynamic and robustness methods. Fuzzy system is the main component of model linear validation system proposed to analyze the results obtained by the tools used in validation stage. System Identification project is performed through operation real data of a pH neutralization pilot plant, located at the Industrial Process Control Laboratory, IPCL, of the Escola Politécnica of the University of São Paulo, Brazil. In order to verify the validation results, all modes are used in QDMC type predictive controller, to follow a set point tracking. The criterions used to assess the QDMC controller performance were the speed response and the process variable minimum variance index, for each model used. The results show that the validation system reliability were 85.71% and 50% projected for low and high non-linearity in a real process, respectively, linking to the performance indexes obtained by the QDMC controller.
Quachio, Raphael. "Análise do algoritmo PLS-PH para identificação de sistemas." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-29062012-145724/.
Повний текст джерелаThe objective of this work consists in evaluating different applications of the PLS-PH (Partial Least Squares Prediction Horizon) algorithm, developed by (LAURI et al., 2010), in order to identify models for MPC controllers. The algorithms capacity of producing linear models capable of performing multiple steps-ahead prediction for both SISO and MIMO systems, with data collected in closed-loop. The algorithms capability of identifying non-linear models with the NARX polynomial structure is also evaluated.
Книги з теми "PH control system"
Kalafatis, Alexandros D. Identification and control of Wiener-type nonlinear systems with applications to pH processes. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1997.
Знайти повний текст джерелаDalbeth, Nicola. Epidemiology. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198748311.003.0003.
Повний текст джерелаЧастини книг з теми "PH control system"
Yano, Takuo, and Yoshinori Nishizawa. "A Simple Automatic Control System of Ph and Do." In Animal Cell Technology: Basic & Applied Aspects, 295–302. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2844-5_41.
Повний текст джерелаLee, Peter L. "An Industrial Application of Reference System Synthesis/Generic Model Control: Wastewater pH Control." In Nonlinear Process Control, 43–65. London: Springer London, 1993. http://dx.doi.org/10.1007/978-1-4471-2079-7_3.
Повний текст джерелаSunori, Sandeep Kumar, Pushpa Bhakuni Negi, Amit Mittal, Bhawana, Pratul Goyal, and Pradeep Kumar Juneja. "Soft Computing-Based Optimization of pH Control System of Sugar Mill." In Expert Clouds and Applications, 271–81. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2126-0_24.
Повний текст джерелаHerriyance, Poltak Sihombing, and Rido Rivaldo. "Development of an Automatic Control System for Controlling of Soil pH Using a Microcontroller." In Advances in Intelligent Systems and Computing, 107–19. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4062-6_10.
Повний текст джерелаAizawa, Peter, Charlotte Benemar, Cecilia Wingenblixt, Kristina Martinelle, and Elisabeth Lindner. "Conventional Stirred Bioreactor Control System for Monitoring and Controlling pH and DO in a Wave Bioreactor." In Cells and Culture, 823–28. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3419-9_144.
Повний текст джерелаKhatri, Narendra, Abhishek Sharma, Kamal Kishore Khatri, and Ganesh D. Sharma. "An IoT-Based Innovative Real-Time pH Monitoring and Control of Municipal Wastewater for Agriculture and Gardening." In Proceedings of First International Conference on Smart System, Innovations and Computing, 353–62. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5828-8_34.
Повний текст джерелаEck, Mathilde, Oliver Körner, and M. Haïssam Jijakli. "Nutrient Cycling in Aquaponics Systems." In Aquaponics Food Production Systems, 231–46. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15943-6_9.
Повний текст джерелаTripetchkul, Sudarut, Michio Tonokawa, Ayaaki Ishizaki, Zhongping Shi, and Kazuyuki Shimizu. "Anaerobic Continuous Ethanol Fermentation using a Computer-Coupled Medium Feeding System Which has DDC Control pH of the Culture Broth." In Developments in Food Engineering, 561–63. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2674-2_180.
Повний текст джерелаGuern, Jean, Yves Mathieu, Geneviève Ephritikhine, Cornelia I. Ullrich-Eberius, Ulrich Lüttge, Maria-Térésa Marré, and Erasmo Marré. "Intracellular pH Modifications Linked to the Activity of the Ferricyanide Driven Activity of the Plasmalemma Redox System in Elodea densa Leaves, Acer pseudoplatanus and Catharanthus roseus Cells." In Plasma Membrane Oxidoreductases in Control of Animal and Plant Growth, 412. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-8029-0_55.
Повний текст джерелаTofail, Syed A. M. "A Dynamically Degradable Surface: Can We ‘Fool’ Bacteria to Delay Biofouling in Urinary Stents?" In Urinary Stents, 187–95. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04484-7_16.
Повний текст джерелаТези доповідей конференцій з теми "PH control system"
Campbell, I., D. Uduehi, A. Ordys, and G. van der Molen. "pH process control system benchmarking." In Proceedings of American Control Conference. IEEE, 2001. http://dx.doi.org/10.1109/acc.2001.945658.
Повний текст джерелаMercader, Pedro, Kristian Soltesz, and Alfonso Banos. "Autotuning of an in-line pH control system." In 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, 2016. http://dx.doi.org/10.1109/etfa.2016.7733588.
Повний текст джерелаHermansson, A. W., S. Syafiiey, and S. B. Mohd Noorz. "Multiple model predictive control of nonlinear pH neutralization system." In EM). IEEE, 2010. http://dx.doi.org/10.1109/ieem.2010.5674469.
Повний текст джерелаHe, Baoxiang, Kaibin Chu, Guirong Lu, Shuyue Chen, and Peng Wang. "A PH complex control system built-in correction factor." In 2010 Sixth International Conference on Natural Computation (ICNC). IEEE, 2010. http://dx.doi.org/10.1109/icnc.2010.5583159.
Повний текст джерелаSingh, Parikshit Kishor, Surekha Bhanot, and Hare Krishna Mohanta. "Optimized adaptive neuro-fuzzy inference system for pH control." In 2013 International Conference on Advanced Electronic Systems (ICAES). IEEE, 2013. http://dx.doi.org/10.1109/icaes.2013.6659349.
Повний текст джерелаTriantino, Septiandi Budi, Anggraini Mulwinda, Arimaz Hangga, Aryo Baskoro Utomo, Nur Azis Salim, and Alim Muanifatin Nisa. "Control System of Nutrient Solution pH Using Fuzzy Logic for Hydroponics System." In 2022 9th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE). IEEE, 2022. http://dx.doi.org/10.1109/icitacee55701.2022.9924108.
Повний текст джерелаDaffa Fadillah, Muhammad, Nanang Ismail, Rina Mardiati, and Ading Kusdiana. "Fuzzy Logic-Based Control System to Maintain pH in Aquaponic." In 2021 7th International Conference on Wireless and Telematics (ICWT). IEEE, 2021. http://dx.doi.org/10.1109/icwt52862.2021.9678404.
Повний текст джерелаLiu, Quanbo, Xiaoli Li, Kang Wang, and Yang Li. "CPS-based Slurry pH Control in Wet Flue Gas Desulfurization System." In 2020 Chinese Control And Decision Conference (CCDC). IEEE, 2020. http://dx.doi.org/10.1109/ccdc49329.2020.9164744.
Повний текст джерелаHermansson, A. W., and S. Syafiie. "Control of pH neutralization system using nonlinear model predictive control with I-controller." In 2014 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2014. http://dx.doi.org/10.1109/ieem.2014.7058759.
Повний текст джерелаTong, Chen, Di Peng, and Yang Jing. "Study on series repairable system reliability model based on PH distribution." In 2017 29th Chinese Control And Decision Conference (CCDC). IEEE, 2017. http://dx.doi.org/10.1109/ccdc.2017.7978933.
Повний текст джерелаЗвіти організацій з теми "PH control system"
Montville, Thomas J., and Roni Shapira. Molecular Engineering of Pediocin A to Establish Structure/Function Relationships for Mechanistic Control of Foodborne Pathogens. United States Department of Agriculture, August 1993. http://dx.doi.org/10.32747/1993.7568088.bard.
Повний текст джерелаRon, Eliora, and Eugene Eugene Nester. Global functional genomics of plant cell transformation by agrobacterium. United States Department of Agriculture, March 2009. http://dx.doi.org/10.32747/2009.7695860.bard.
Повний текст джерелаLahav, Ori, Albert Heber, and David Broday. Elimination of emissions of ammonia and hydrogen sulfide from confined animal and feeding operations (CAFO) using an adsorption/liquid-redox process with biological regeneration. United States Department of Agriculture, March 2008. http://dx.doi.org/10.32747/2008.7695589.bard.
Повний текст джерелаShomer, Ilan, Ruth E. Stark, Victor Gaba, and James D. Batteas. Understanding the hardening syndrome of potato (Solanum tuberosum L.) tuber tissue to eliminate textural defects in fresh and fresh-peeled/cut products. United States Department of Agriculture, November 2002. http://dx.doi.org/10.32747/2002.7587238.bard.
Повний текст джерелаSionov, Edward, Nancy Keller, and Shiri Barad-Kotler. Mechanisms governing the global regulation of mycotoxin production and pathogenicity by Penicillium expansum in postharvest fruits. United States Department of Agriculture, January 2017. http://dx.doi.org/10.32747/2017.7604292.bard.
Повний текст джерелаDroby, Samir, Michael Wisniewski, Ron Porat, and Dumitru Macarisin. Role of Reactive Oxygen Species (ROS) in Tritrophic Interactions in Postharvest Biocontrol Systems. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7594390.bard.
Повний текст джерелаPrusky, Dov, Nancy P. Keller, and Amir Sherman. global regulation of mycotoxin accumulation during pathogenicity of Penicillium expansum in postharvest fruits. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7600012.bard.
Повний текст джерелаDelwiche, Michael, Boaz Zion, Robert BonDurant, Judith Rishpon, Ephraim Maltz, and Miriam Rosenberg. Biosensors for On-Line Measurement of Reproductive Hormones and Milk Proteins to Improve Dairy Herd Management. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7573998.bard.
Повний текст джерелаAvnimelech, Yoram, Richard C. Stehouwer, and Jon Chorover. Use of Composted Waste Materials for Enhanced Ca Migration and Exchange in Sodic Soils and Acidic Minespoils. United States Department of Agriculture, June 2001. http://dx.doi.org/10.32747/2001.7575291.bard.
Повний текст джерелаBowles, David, Michael Williams, Hope Dodd, Lloyd Morrison, Janice Hinsey, Tyler Cribbs, Gareth Rowell, Michael DeBacker, Jennifer Haack-Gaynor, and Jeffrey Williams. Protocol for monitoring aquatic invertebrates of small streams in the Heartland Inventory & Monitoring Network: Version 2.1. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2284622.
Повний текст джерела