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Journal articles on the topic 'PH control system'

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Author: Grafiati

Published: 6 September 2023

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1

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.

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2

Ooi, 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.

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Abstract This paper studies the feasibility of using discrete sliding mode controller (SMC) to achieve offset-free control of nonlinear processes in the presence of disturbances. The performance of the SMC is compared to a multiple model predictive controller (MMPC) studying the ability of set-point tracking using the pH system as a case study. The results presented from the comparison show that SMC can perform offset-free control of a pH system, with the major drawback being slow response as well as oscillation at some pH values. Finally, a design of a combination between MMPC and SMC (MMPC-SMC) is proposed, with MMPC carrying out basic control response while the SMC fulfils the role of eliminating the offset. However, the inaccurate reading in the MATLAB simulation model does not generate the expected results on the pH control. Therefore, the modification on the MATLAB models is required to achieve the improved control system on the offset-free behaviour for the set-point tracking.

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Safira, 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.

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Abstract In hydroponic farming, optimal pH value is important to regulate nutrient availability for efficient plant growth. This study aims to design an autonomous pH monitoring and control system for maintaining an optimal pH range. The prototype was developed for data acquisition, data processing and data visualization to ensure that the measured nutritional solution parameters are within the specified range: temperature (18–35°C), pH (5.5–8.0), and dissolved oxygen level (>2 ppm). Data collected at sampling rate of 10 seconds utilising temperature sensor, pH sensor, and dissolved oxygen sensor were processed using a microcontroller on a Node-RED interface in a Raspberry Pi. The processed data were stored in InfluxDB before being displayed in Grafana. If the value exceeded the threshold, a Telegram alert was delivered to the end-user. The pH data were used to build a framework to control the pH levels within range. Two peristaltic pumps (DFRobot, DFR0523) were utilized to pump potassium hydroxide or phosphoric acid solution if the pH was out of range. The developed prototype was able to automatically control the pH within the optimum range in the nutrient solution, which will positively impact the nutrient adsorption and subsequent plant growth in a hydroponics system.

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4

Castanie-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.

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ABSTRACT Acid resistance (AR) in Escherichia coli is defined as the ability to withstand an acid challenge of pH 2.5 or less and is a trait generally restricted to stationary-phase cells. Earlier reports described three AR systems in E. coli. In the present study, the genetics and control of these three systems have been more clearly defined. Expression of the first AR system (designated the oxidative or glucose-repressed AR system) was previously shown to require the alternative sigma factor RpoS. Consistent with glucose repression, this system also proved to be dependent in many situations on the cyclic AMP receptor protein. The second AR system required the addition of arginine during pH 2.5 acid challenge, the structural gene for arginine decarboxylase (adiA), and the regulatorcysB, confirming earlier reports. The third AR system required glutamate for protection at pH 2.5, one of two genes encoding glutamate decarboxylase (gadA or gadB), and the gene encoding the putative glutamate:γ-aminobutyric acid antiporter (gadC). Only one of the two glutamate decarboxylases was needed for protection at pH 2.5. However, survival at pH 2 required both glutamate decarboxylase isozymes. Stationary phase and acid pH regulation of the gad genes proved separable. Stationary-phase induction of gadA and gadBrequired the alternative sigma factor ςS encoded byrpoS. However, acid induction of these enzymes, which was demonstrated to occur in exponential- and stationary-phase cells, proved to be ςS independent. Neither gad gene required the presence of volatile fatty acids for induction. The data also indicate that AR via the amino acid decarboxylase systems requires more than an inducible decarboxylase and antiporter. Another surprising finding was that the ςS-dependent oxidative system, originally thought to be acid induced, actually proved to be induced following entry into stationary phase regardless of the pH. However, an inhibitor produced at pH 8 somehow interferes with the activity of this system, giving the illusion of acid induction. The results also revealed that the AR system affording the most effective protection at pH 2 in complex medium (either Luria-Bertani broth or brain heart infusion broth plus 0.4% glucose) is the glutamate-dependent GAD system. Thus, E. coli possesses three overlapping acid survival systems whose various levels of control and differing requirements for activity ensure that at least one system will be available to protect the stationary-phase cell under naturally occurring acidic environments.

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5

KOBAYASHI, 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.

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6

Grancharova, 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.

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Abstract In this paper the problem of optimal regulation of a pH maintaining system is considered, where the outputs are the pH value and the liquid level in the system and the control inputs are the flow rates of the base input flow and the output flow. The optimal regulation problem is formulated as a nonlinear model predictive control problem in the presence of constraints. Two cases are considered: 1) presence of box constraints only on the control inputs and 2) considering also constraints on the rate of change of the inputs.

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7

Palancar, 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.

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8

Agustian, 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.

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The Nutrient Film Technique (NFT) method is one of the most popular hydroponic cultivation methods. This method has advantages such as easier maintenance, faster and optimal plant growth, better use of fertilizers, and less deposition. The disadvantages of NFT include the consumption of electrical power and the faster spread of disease. Therefore, NFT requires a good nutrient control and monitoring system to save electricity and achieve optimal growth and resistance to pests and diseases. In this study, a nutrient control was designed with indicators of pH and TDS levels and equipped with an Internet of Things (IoT) based monitoring system. The control system used is the Mamdani Fuzzy Inference System. The output of the system is the active time of the pH Up, pH Down, and AB Mix nutrient pumps, which aim to normalize the pH and TDS of nutrient liquids. The experimental results show that one to three control steps are needed to normalize pH. One control step has a response time of 60 seconds, and it can prevent pH Up and pH Down oscillations. As for TDS control, the prediction of AB mix pump active time works accurately, and TDS levels can be normalized in one control step. Overall, based on surface control, simulations, and real experimental data, it is indicated that the control system operates very well and can normalize pH and TDS to the desired normal standard.

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9

Qian, 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.

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pH parameter is one of the main factors influencing organic degradation in the sewage treatment, and the degradation of organic matter in biochemical treatment unit is the largest, the hydrolysis acidification processing unit is the second largest. When the water pH range of biochemical treatment unit is [6.8 7.2], organic degradation is in the largest degree. The pH range of neutralization unit must be based on a subsequent hydrolysis acidification treatment unit, in order to adjust the pH range dynamically. Finally we make wastewater treated by biochemical unit meet the pH standard, and make the organic matter degrade in the largest degree. We designed chemical wastewater pH intelligent control device based on MSP430F149 MCU. The application of this device shows that the method has high control accuracy, less drug consumption and has large organic matter degradation in the sewage treatment plant, etc.

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10

Klimenok, 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.

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11

Ibáñez, Jorge G., Luis Tavera, Alberto Rodriguez, and Enrique Gomez del Campo. "A pH-monitoring and control system for teaching laboratories." Journal of Chemical Education 67, no. 3 (March 1990): A74. http://dx.doi.org/10.1021/ed067pa74.2.

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12

Hermansson, A. W., and S. Syafiie. "Offset-free control of a pH system using Multiple Model Predictive Control." IOP Conference Series: Materials Science and Engineering 778 (May 1, 2020): 012072. http://dx.doi.org/10.1088/1757-899x/778/1/012072.

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13

Gunung, I. Nyoman, I. Nengah Ludra Antara, I. Nyoman Sutarna, Kadek Agus Mahabojana D. P., and Made Dika Nugraha. "Simulation Design Of Animal Waste Treatment Installation System Using Water Level Control System." LOGIC : Jurnal Rancang Bangun dan Teknologi 23, no. 1 (March 31, 2023): 8–15. http://dx.doi.org/10.31940/logic.v23i1.8-15.

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The simulation design of this animal waste treatment plant is a design that applies the sewage treatment plant system which is made to cope with environmental pollution, especially rivers due to indiscriminate disposal of animal waste. Making this animal waste treatment plant provides information to readers or the public about how to design an animal waste treatment plant system and the performance of the sewage treatment system so that people know how to deal with environmental pollution caused by the livestock themselves. The manufacture of this installation system uses data collection methods from direct farmers and theories obtained from books, journals, articles related to sewage treatment plant theory, plumbing, electricity, and others. Finally, the data was collected by testing the animal dung waste treatment system where the test data was taken from the pH content of the water used for processing the animal dung waste treatment system. The test results on the sewage treatment plant system concluded that in order to obtain optimal results or water pH content, namely the pH content of 6, it is necessary to deposit animal manure between two to three days, while the maximum processing of this system is the pH content of 6.5. and processing of animal manure, which is on the fourth day to get the maximum pH content.

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14

Huang, Song Wei, Ge Peng, and Li Fang He. "Automatic Control of Pulp pH Value." Applied Mechanics and Materials 644-650 (September 2014): 684–88. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.684.

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Control of pulp pH value is the key step in the process of washing zinc oxide. Due to the characteristics of large time delay and strong nonlinear, the control of pulp pH value is very difficult. In this paper, aiming at the above problem and according to the features of washing operation of zinc oxide powder, design a control system of a fuzzy controller, secondary fuzzy controller and PI controller.

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15

Guo, Shan Shan, and Ze Dong. "Application of DMC Algorithm on pH Control of WFGD System." Applied Mechanics and Materials 568-570 (June 2014): 1090–94. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.1090.

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The paper studies on wet flue gas desulfurization process and the factors of affecting the desulfurization efficiency, and analyses the control system of the absorber slurry pH value. The conventional PID control is difficult to achieve satisfactory control effect, so it puts forward the predictive control scheme based on Dynamic Matrix Control (DMC) algorithm to identify and control the change of pH value. Simulation results show that under the control of DMC algorithm, the slurry pH value has a good tracking for setting input and its changes , reflecting a high degree of adaptability. The control with low overshoot and good accuracy is better than conventional PID control and meets the requirements of real-time control.

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16

Yasin, Muhammad Naqiuddin Mohamad. "Freshwater pH Level Control and GUI System for Prawn Breeding." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 4 (August 25, 2020): 5887–93. http://dx.doi.org/10.30534/ijatcse/2020/250942020.

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17

Enoch, C. R. T., and J. Evans. "NOVEL PH CONTROL SYSTEM SAVES WATER TREATMENT FACILITY 250K pa." Proceedings of the Water Environment Federation 2001, no. 15 (January 1, 2001): 287–310. http://dx.doi.org/10.2175/193864701790902563.

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18

Harivardhagini, S. "LabVIEW based Sliding Mode Control of a pH Neutralization System." CVR Journal of Science & Technology 10, no. 1 (June 1, 2016): 70–73. http://dx.doi.org/10.32377/cvrjst1015.

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19

Meenakshipriya, B., K. Saravanan, S. Somasundaram, and P. Kanthabhabha. "CDM-BASED PI-P CONTROL STRATEGY IN pH NEUTRALIZATION SYSTEM." Instrumentation Science & Technology 39, no. 3 (May 2011): 273–87. http://dx.doi.org/10.1080/10739149.2011.564701.

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20

Obut, Salih, and Canan Özgen. "Online Identification and Control of pH in a Neutralization System." Industrial & Engineering Chemistry Research 47, no. 13 (July 2008): 4394–404. http://dx.doi.org/10.1021/ie070492p.

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21

Sun, Rong Xia, Pan Pan Huang, Ning Ran, Jian Kang, Xiao Feng Chen, and Yi Tian. "Design and Realization of Monitoring System for Multiway pH Value." Advanced Materials Research 383-390 (November 2011): 6–11. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.6.

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Multi-PH value system detecting system is maked with AT89C52 MCU as the control center. Detecting uses pH-BTA sensor, signals are amplificated through CA3140, ADC0808 realizes A/D conversion, 74LS148 controls 8 signals acquisition, 1602 LCD displays PH value, remote data monitoring in PC is realized through serial port. Adopt VB to monitoring interface in PC. Physical production and debugging is accomplished based on the simulation in proteus, 8 pH values of real-time and cycle monitoring system is realized ultimately. Actual test data shows that the error of measuring pH value and theoretical pH value is between ± 0.1 relatively.

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22

Al Tahtawi, Adnan Rafi, and Robi Kurniawan. "PH control for deep flow technique hydroponic IoT systems based on fuzzy logic controller." Jurnal Teknologi dan Sistem Komputer 8, no. 4 (October 13, 2020): 323–29. http://dx.doi.org/10.14710/jtsiskom.2020.13822.

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In hydroponic cultivation sites, pH control is still carried manually by checking the pH level with a pH meter and providing a pH balancing liquid manually. This study aims to design an automatic pH control system in the Deep Flow Technique (DFT) hydroponic system that uses the Internet of Things (IoT) based Fuzzy Logic Controller (FLC). The SKU SEN0161 sensor detects the pH value as FLC inputs in an error value and its changes. These inputs are processed using Mamdani FLC embedded in the Arduino Mega 2560 microcontroller. The FLC produces an output in a pH liquid feeding duration using the peristaltic pump. The results showed that FLC could maintain the pH value according to the set point with a settling time of less than 50 seconds, both with disturbance by adding pH liquid and without disturbance. The pH value can also be displayed on the website interface system as a monitoring system.

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23

Hong, Zhang, Shou Sheng Zhang, and Lu Ping Sang. "Research on Application of Distributed Control System in Industrial Process Control." Applied Mechanics and Materials 427-429 (September 2013): 842–45. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.842.

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By combination with the general structure characteristics of the distributed control system and the technical specifications of CAN bus, this paper puts forward, designs a FDCS model control system for sewage treatment based on CAN bus and establishes mathematic model for dissolved oxygen (DO) and pH value in the oxidation ditch. It also designs two self-adaptive algorithms of the model and performs digital simulation of the control algorithms.

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24

Lee, Jung-Sup, Ji-Ho Choi, Sang-Tae Seo, Kyoung-Suk Han, Jong-Han Park, and Han-Ik Jang. "Control of Tomato Wilt Disease by Amending pH of Nutrient Solution in Hydroponic System." Research in Plant Disease 11, no. 2 (December 1, 2005): 193–97. http://dx.doi.org/10.5423/rpd.2005.11.2.193.

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25

Srour, T., Ayman Haggag, Mohsen A. M., Ibrahim Saber, and A. E. Abou Elazm. "QUALITY CONTROL CONSIDERATION: EFFICIENT REAL-TIME WATER MONITORING UTILIZING MULTI-SENSORS AND ICT CONCEPTS." International Journal of Research -GRANTHAALAYAH 6, no. 10 (October 31, 2018): 240–55. http://dx.doi.org/10.29121/granthaalayah.v6.i10.2018.1191.

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Design efficient an interactive system for water pollution monitoring and quality control is proposed in this paper utilizing different sensors and employing Information Communication Technology (ICT). The presented system is built based on the pH and temperature water parameters. The system consists of sensors, Arduino controller and designed Graphical User Interface (GUI). GUI is designed to display the parameters values and control option. The operator can control the parameters values through operating control systems by a set of control switches in GUI. For example, the result of pH parameter during the monitoring = 7.06, while after operating the control system the pH parameter = 10.16. This result shows the ability of the system to monitor and control of water parameters. Different water parameters and properties are discussed in this paper also.

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26

Agrawal, Palash, Sankalp Bhagwate, Dhruv Singhaniya, Aditi Tamrakar, and Prof Puja S. Agrawal. "Automated Hydroponics System." International Journal for Research in Applied Science and Engineering Technology 11, no. 3 (March 31, 2023): 1718–26. http://dx.doi.org/10.22214/ijraset.2023.49606.

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Abstract: The purpose of this study was to control the factors that are responsible for plants growth in hydroponics systems and automate them to reduce the human effort with less space and electricity. In this paper we used a combination of two methods: Deep water culture and Nutrient film technique for the system. In this method plants will have continuous nutrient supply. We used a linear regression method to control EC and pH of the system and the microcontroller will send signals to the system to adjust them to desired value with the help of dozers by taking average EC and pH values.

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27

Tiga, Marianus. "Automatic Wastewater Control System for Soil Fertility use Fuzzy Logic and IoT-Based." Internet of Things and Artificial Intelligence Journal 1, no. 3 (September 15, 2021): 176–97. http://dx.doi.org/10.31763/iota.v1i3.500.

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The process of controlling the flow of waste in irrigation canals is one form of effort to support the sustainability of plant growth on garden beds. Farmers use many strategies or efforts to maintain fertility and plant growth to obtain more increased and productive yields. Based on research, clean water from rivers in irrigation canals that pass through residential areas to produce wastewater before it reaches plants. Moreover, a process, less healthy for plant growth than clean water irrigation channels with normal pH (Potential Hydrogen) required by plants. Setting pH and soil moisture according to plant needs, i.e., 6.5-7 for water pH and 50%-70% for soil moisture. This value is the best step in plant growth care; an irrigation canal is made that can measure water pH using sensor pH and soil moisture by using a soil moisture sensor and can normalize water pH and soil moisture according to plant needs. The pH down pump automatically pours acidic pH when the pH reading is alkaline and vice versa; the up pump automatically pours acid when the pH reading is acidic. To measure the water level in the reservoir, use an ultrasonic sensor to not seep out of the reservoir because it is full. This tool is equipped with a pump to channel water from the wastewater reservoir to the water pH measurement reservoir and proceed to the plants, where fuzzy logic works to regulate the speed of the plant watering pump with input obtained from soil moisture sensor readings and temperature sensors. Finally, control using the Esp32 MCU Node by being monitored using the Blynk application displayed on the android.

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28

Lívanský, Karel, and Miroslav Kajan. "Relationship between pCO2 and pH in batch algal cultures as a basis for an estimation of pCO2 control by means of a pH-stat system." Algological Studies/Archiv für Hydrobiologie, Supplement Volumes 74 (September 30, 1994): 105–19. http://dx.doi.org/10.1127/algol_stud/74/1994/105.

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29

AlSabbah, Shebel, Mujahed AlDhaifallah, and Mohammad Al-Jarrah. "Design of Multiregional Supervisory Fuzzy PID Control of pH Reactors." Journal of Control Science and Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/396879.

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This work concerns designing multiregional supervisory fuzzy PID (Proportional-Integral-Derivative) control for pH reactors. The proposed work focuses, mainly, on two themes. The first one is to propose a multiregional supervisory fuzzy-based cascade control structure. It would enable modifying dynamics and enhance system’s stability. The fuzzy system (master loop) has been chosen as a tuner for PID controller (slave loop). It takes into consideration parameters uncertainties and reference tracking. The second theme concerns designing a hybrid neural network-based pH estimator. The proposed estimator would overcome the industrial drawbacks, that is, cost and size, found with conventional methods for pH measurement. The final end-user-interface (EUI) front panel and the results that evaluate the performance of the supervisory fuzzy PID-based control system and hybrid NN-based estimator have been presented using the compatibility found between LabView and MatLab. They lead to conclude that the proposed algorithms are appropriate to systems nonlinearities encountered with pH reactors.

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30

Basri, Muhammad, and Joi Alfreddi Surbakti. "Rancang Bangun Akuarium Portable Menggunakan Teknologi Internet Of Things Untuk Budidaya Ikan Hias." Jurnal Teori dan Aplikasi Fisika 11, no. 01 (February 20, 2023): 47–54. http://dx.doi.org/10.23960/jtaf.v10i2.3146.

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Portable aquarium designed with an automation system for controlling pH levels and temperature information. pH levels are measured using a pH sensor E-201-C and temperature is measured with a DS18B20 sensor. The pH control process is carried out by adding liquid pH up and pH down and is realized with a solenoid valve. The purpose of making this portable aquarium is to control the pH value of the water in the aquarium and provide information about the water temperature. Into this portable aquarium system have been inputted standard values of pH and temperature for each type of fish. This system will work automatically to adjust the living environment of ornamental fish according to their respective needs. The pH control system can work if the pH measurement value indicates a high pH or low pH condition and under these conditions, the water will flow into the pH adjustment tube to control. If the pH measurement value states that the pH is high then the pH down control liquid will flow and if the pH measurement value states that the pH is low then the pH up control liquid will flow. This system has been proven to be able to maintain the environmental conditions of ornamental fish with the results of pH and temperature measurements being 7.48 -7.8 and 28.87 – 29.55 °C.

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Sri Lestari, Veronika Nugraheni, Dwi Cahyono, and Sri Susilowati. "Designing Early Warning System for The Impact of Industrial Development Waste by Using pH Control System." International Journal of Engineering & Technology 7, no. 2.14 (April 15, 2018): 555. http://dx.doi.org/10.14419/ijet.v7i2.11581.

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Environment is inseparable from human life. Human negligence in building industry without caring the impact on environment can damage the physical and biological environment slowly and indirectly. Therefore an effort to preserve the quality of environment, especially for the environment adjacent to the settlement, is necessary and can be performed in various ways including technology utilization. Technology develops rapidly and electronic devices have become one compulsory device to be owned. Wastewater is industrial waste should be controlled prior to passing surrounding environment to avoid pollution. One way to control it is controlling its pH of, this is performed by early warning on pH level. This paper focused on designing control device for industrial waste water pH that is able to inform an early when on concentration of industrial waste water under normal limit water.

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32

Zhou, Haiying, Jennifer Purdie, Tongtong Wang, and Anli Ouyang. "pH measurement and a rational and practical pH control strategy for high throughput cell culture system." Biotechnology Progress 26, no. 3 (December 28, 2009): 872–80. http://dx.doi.org/10.1002/btpr.369.

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33

Rathedi, Maemo, Oduetse Matsebe, and Nonofo M. J. Ditshego. "Performance Evaluation of Hydroponics Control Systems for pH, Temperature, and Water Level Control." International Journal of Engineering Research in Africa 65 (August 8, 2023): 105–16. http://dx.doi.org/10.4028/p-rbt3yu.

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This study evaluates different control algorithms used in a hydroponic farming system to improve the quality of farm produce and resource efficiency. It focuses on three key hydroponic control parameters(potential hydrogen (pH), water level, and temperature control). Mathematical models are derived from the literature to represent hydroponic environments. These models are used for simulation purposes in MATLAB software to implement various control algorithms to evaluate their performance against each other and the system requirements utilizing transient performance parameters. Transient performance parameters are overshoot, settling time, rise time ,and steady-state error. The various control algorithms are fuzzy logic (FL), Proportional Integral Derivative (PID), and Proportional Integral Derivative-Fuzzy logic controller (PID-FL). This paper examines the performance of the hybrid PID-FL controllers compared to the most commonly used fuzzy logic and PID controllers. The result of the work shows that PID-FL is generally better for all the system models, making it more applicable.

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34

Firmansyah, Deni, Ibrahim Lammada, and Gina Lova Sari. "IMPLEMENTATION OF AUTOMATIC PUMP CONTROL ON SEA WATER DESTILATION SYSTEM." Electro Luceat 6, no. 2 (November 3, 2020): 299–307. http://dx.doi.org/10.32531/jelekn.v6i2.268.

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This study aims to design an automatic pump control system and assess the effectiveness of using pumps in seawater distillation systems. The system uses an Arduino Uno microcontroller for central control of all system activities and a relay as a pump switch. Ultrasonic sensors, pH sensors and TDS sensors as input to provide information on the condition of the water in the storage container, the water pump as an output for pumping and flowing sea water and distilled water. The water pump in the seawater distillation system is used to drain seawater to the initial reservoir with a water level set point >20cm, if the set point is met, the pump will turn on. The second mini pump is used to flow the distilled water to the final reservoir with a set point value of pH <8 and a TDS value <1400, so the pump will turn on. The third mini pump is used to flow distilled water to the second basin with a set point value of pH >8 and a value of TDS >1400, so the pump will turn on, therefore the use of a pump in an automatic seawater distillation system is needed and its use can be said to be effective. Keywords: Water Pump, Relay, Control

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35

YAhmed, S., S. E Amin, and T. Alarif. "Efficient Cooperative Control System for pH Sensitive Nanorobots in Drug Delivery." International Journal of Computer Applications 103, no. 1 (October 18, 2014): 39–43. http://dx.doi.org/10.5120/18042-8947.

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36

NAGASE, Makoto, Kazushige ISHIDA, Naohito UETAKE, Kazumi ANAZAWA, Fumito NAKAMURA, Hiroo YOSHIKAWA, Tadashi TAMAGAWA, and Kiyoharu FURUKAWA. "Low Corrosive Chemical Decontamination Method Using pH Control, (I) Basic System." Journal of Nuclear Science and Technology 38, no. 12 (December 2001): 1090–96. http://dx.doi.org/10.1080/18811248.2001.9715140.

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37

Ben-Hassan, R. M., A. E. Ghaly, and M. H. Mansour. "A computer-based ph measurement and control system for fermentation processes." Applied Biochemistry and Biotechnology 30, no. 3 (September 1991): 233–45. http://dx.doi.org/10.1007/bf02922028.

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38

Menzl, Stefan, Michael Stühler, and Roland Benz. "A self adaptive computer-based pH measurement and fuzzy-control system." Water Research 30, no. 4 (April 1996): 981–91. http://dx.doi.org/10.1016/0043-1354(95)00249-9.

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39

Pawlowski, A., J. L. Guzmán, M. Berenguel, and F. G. Acién. "Control System for pH in Raceway Photobioreactors Based on Wiener Models." IFAC-PapersOnLine 52, no. 1 (2019): 928–33. http://dx.doi.org/10.1016/j.ifacol.2019.06.181.

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40

Zhang, Xingchao, Jianhong Liu, and Peng Hu. "Research on Control Method of Wet Desulfurization System for Coal-fired Boiler." Journal of Physics: Conference Series 2076, no. 1 (November 1, 2021): 012063. http://dx.doi.org/10.1088/1742-6596/2076/1/012063.

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Abstract In wet flue gas desulfurization technology, the key factor affecting flue gas SO2 absorption is the control of slurry pH value in the absorption tower. However, most of the commonly used pH value control methods have some defects and cannot fully meet the system control requirements. On the basis of the analysis for the problems in the control process, this paper discussed a control strategy based on internal model control algorithm. The system simulation test showed that this control method had good dynamic performance, robustness and anti-interference, which could realize the relatively accurate control of pH value for wet flue gas desulfurization system, and achieve the control goal.

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41

Malik, Chorina Rosa, Imam Sucahyo, and Meta Yantidewi. "Automation of Microcontroller-Based Control System for Ph, Temperature, and Turbidity of Aquarium Water." Prisma Sains : Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram 10, no. 3 (July 8, 2022): 700. http://dx.doi.org/10.33394/j-ps.v10i3.5455.

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This research is an experimental study to know the effectiveness of the control system for pH, temperature, and turbidity of aquarium water in ornamental fish cultivation. The method used is by assembling an automation tool for controlling the pH, temperature, and turbidity of the aquarium water based on a microcontroller, which is then compared with an aquarium without a control system. This tool is designed using the Arduino Uno as a system controller, the pH sensor E-201-C as a measuring tool for pH levels with a solenoid valve to drain pH up and pH down as a stabilizer for water pH levels, the DS18B20 sensor as a temperature measurement tool by utilizing a heater and DC fan as a water temperature stabilizer, and the turbidity sensor as a turbidity measurement tool with a clean water replacement system as a water turbidity stabilizer. Based on the experiments carried out, it was found that there were significant differences between aquariums using a control system automation tool compared to aquariums without a control system tool. This means that the system that is made is effective and proven to be able to maintain the environmental conditions of ornamental fish with measurement results of pH ranging from 7–7.5, the temperature of 24°–27°C, and water turbidity of 10 NTU.

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Kurniawan, Lutfi Athanuzul, and Amirullah Amirullah. "Monitoring and Controlling of pH Levels and Plant Nutrition Supplied by Standalone Photovoltaic in a Greenhouse Hydroponic System using Arduino Uno." ELKHA 13, no. 1 (April 20, 2021): 69. http://dx.doi.org/10.26418/elkha.v13i1.45657.

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This paper aims to implement the prototype model to monitor and control the pH levels and nutrition plant (electrical conductivity-EC) supplied by a standalone photovoltaic (PV) module-connected battery (Lithium-Ion) on the greenhouse hydroponic systems. The pH and EC sensors are connected to the Arduino Uno circuit as a relay control to drive four pumps, i.e. the water flow pump, EC pump, pH up pump, and pH down pump. The greenhouse function to control pests and the impact of environmental non-uniformity caused by variation of wind speed, temperature, or sunlight so that hydroponic plants can grow in an appropriate environment. The Arduino Uno circuit with a 20 × 4 liquid crystal display (LCD) order four relays to monitor and control the four pumps of the greenhouse hydroponic system based on the coding which has been programmed previously. The prototype model is able to monitor and control the pH of hydroponic plant water at the level between 6-7 using a pH-up and pH-down sensor. This model is also able to monitor and control nutrition plant water over 1 mS/cm using an EC sensor. Finally, the proposed prototype is able to monitor and control EC and pH level to regulate plant growth in the greenhouse hydroponic system normally and in real-time.

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Indriani, Anizar, and Marhalim Fajri. "Kontrol Kualitas Kadar Air Laut Menggunakan Fuzzy LogicUntuk Habitat Ikan Kerapu." JTEV (Jurnal Teknik Elektro dan Vokasional) 5, no. 1.1 (September 25, 2019): 77. http://dx.doi.org/10.24036/jtev.v5i1.1.106151.

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The quality of the seawater content for the grouper fish habitat is very influential in the grouper fish development process. Seawater quality for grouper fish habitat depend on temperatur, salinity, acidity (pH), and turbidity of seawater. The quality of seawater can be control by circulation in and out of seawater in the fish pond. This cycle is required to maintain the desired quality of seawater at temperatur 24ºC- 31ºC, salinity 30-33 ppt, dissolved oxygen> 3,5 ppt, and pH 7,5-8,3. In previous studies seawater control systems have been carried out in the form of controls temperatur and pH quality. Other components quality of sea water such as salinity and turbidity due to fish food also influence seawater quality for grouper fish habitat. Component control of sea water in this paper include microcontroller, pump sea water, fresh water pump, sensor and etc. In this paper we are focus on the controlling sea water quality to maintain the quality of grouper fish pools consisting of temperatur, salinity, acidity (pH), and turbidity of seawater. Input this data and the pH of the water read by the sensor will be processed with fuzzy logic to adjust the working of the salt water pump and the freshwater pump until it reaches the setpoint value. Turbidity and temperatur control using the ON-OFF system. The results show that of testing the sea water quality of control system using fuzzy logic in accordance with the calculation of mathematical defuzzyfication with an error of 0%. The values of salinity control system 31,14-32,98 PPT, pH 7,78-8,.2, temperatur 27ºC-29,98ºC, and turbidity level 9,90-14,85 NTU.

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Fikri, Sauthul, Arief Budi Laksono, and Ulul Ilmi. "THE NUTRITION INTAKE CONTROL TOOLS IN HYDROPONIC USING MICROCONTROLLER." JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) 4, no. 1 (July 27, 2021): 09–14. http://dx.doi.org/10.26905/jeemecs.v4i1.4412.

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The development of the world of technology combined with agricultural science can benefit farmers and, of course, the community. one of them is farming through the Hydroponic system, the purpose of this study is to find out how to make nutrition control devices on the Pakcoy hydroponics using a microcontroller on hydroponics. The method used includes electrical design, systematic, in order to obtain accurate data and information. This study using the stages of designing hardware and software and integrating the system and the system testing stage. This test uses a pH meter, where the sensor detects a pH with a value of 6-7 pH, and when the pH sensor detects a value below six, it will automatically add nutrients. As well as water temperature and room temperature will regulate the temperature in the water by turning on the waterwheel in the reservoir automatically. Furthermore, all results are sent to the ThinkSpeak application via an IoT server. The display produced on ThinkSpeak is the water temperature, room temperature, water temperature, and water pH.

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Shimizu, Hiroshi, Taiji Mizuguchi, Eiji Tanaka, and Suteaki Shioya. "Nisin Production by a Mixed-Culture System Consisting of Lactococcus lactis andKluyveromyces marxianus." Applied and Environmental Microbiology 65, no. 7 (July 1, 1999): 3134–41. http://dx.doi.org/10.1128/aem.65.7.3134-3141.1999.

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ABSTRACT To control the pH during antimicrobial peptide (nisin) production by a lactic acid bacterium, Lactococcus lactis subsp.lactis (ATCC11454), a novel method involving neither addition of alkali nor a separation system such as a ceramic membrane filter and electrodialyzer was developed. A mixed culture of L. lactis and Kluyveromyces marxianus, which was isolated from kefir grains, was utilized in the developed system. The interaction between lactate production by L. lactis and its assimilation by K. marxianus was used to control the pH. To utilize the interaction of these microorganisms to maintain high-level production of nisin, the kinetics of growth of, and production of lactate, acetate, and nisin by, L. lactis were investigated. The kinetics of growth of and lactic acid consumption byK. marxianus were also investigated. Because the pH of the medium could be controlled by the lactate consumption of K. marxianus and the specific lactate consumption rate of K. marxianus could be controlled by changing the dissolved oxygen (DO) concentration, a cascade pH controller coupled with DO control was developed. As a result, the pH was kept constant because the lactate level was kept low and nisin accumulated in the medium to a high level compared with that attained using other pH control strategies, such as with processes lacking pH control and those in which pH is controlled by addition of alkali.

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46

Rodríguez-Torres, María José, Ainoa Morillas-España, José Luis Guzmán, and Francisco Gabriel Acién. "Modelling and pH Control in Raceway and Thin-Layer Photobioreactors for Wastewater Treatment." Energies 14, no. 4 (February 19, 2021): 1099. http://dx.doi.org/10.3390/en14041099.

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One of the most critical variables in microalgae-related processes is the pH; it directly determines the overall performance of the production system especially when coupling with wastewater treatment. In microalgae-related wastewater treatment processes, the adequacy of pH has a large impact on the microalgae/bacteria consortium already developing on these systems. For cost-saving reasons, the pH is usually controlled by classical On/Off control algorithms during the daytime period, typically with the dynamics of the system and disturbances not being considered in the design of the control system. This paper presents the modelling and pH control in open photobioreactors, both raceway and thin-layer, using advanced controllers. In both types of photobioreactors, a classic control was implemented and compared with a Proportional–Integral (PI) control, also the operation during only the daylight period and complete daily time was evaluated. Thus, three major variables already studied include (i) the type of reactors (thin-layers and raceways), (ii) the type of control algorithm (On/Off and PI), and (iii) the control period (during the daytime and throughout the daytime and nighttime). Results show that the pH was adequately controlled in both photobioreactors, although each type requires different control algorithms, the pH control being largely improved when using PI controllers, with the controllers allowing us to reduce the total costs of the process with the reduction of CO2 injections. Moreover, the control during the complete daily cycle (including night) not only not increases the amount of CO2 to be injected, otherwise reducing it, but also improves the overall performance of the production process. Optimal pH control systems here developed are highly useful to develop robust large-scale microalgae-related wastewater treatment processes.

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Zulkarnain, Muhammad. "Design of Media Humidity Control System in Earthworm Cultivation." Jurnal Jartel: Jurnal Jaringan Telekomunikasi 9, no. 4 (December 25, 2019): 31–35. http://dx.doi.org/10.33795/jartel.v9i4.152.

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An important factor in worm cultivation is the humidity of the media, in practice for breedersthe worm regulates the humidity of the media by feeling the moisture with your hands, then when you feel it is dry then it is doused with water. In this study, a system will be made to determine the conditions of air temperature, air humidity, soil moisture, and soil pH in the worm habitat. Besides that, it also has an actuator as an automatic sprinkler when the humidity is dry. Monitoring results will be sent via the website. From the results of the research for 30 days, it was found that the humidity value at the node with the automatic sprinkler actuator had a more stable and optimal level of media humidity compared to conventional methods with a 10% difference in value. Meanwhile, the temperature and pH values ??tend to be the same. The yield on beds without actuators is 0.8 kg, while in beds with actuators it is 1.1 kg.

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Ruģele, Kristīne, Girts Bumanis, Diana Bajare, Vitalijs Lakevičs, and Jānis Rubulis. "Alkaline Activated Material for pH Control in Biotechnologies." Key Engineering Materials 604 (March 2014): 223–26. http://dx.doi.org/10.4028/www.scientific.net/kem.604.223.

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By using industrial aluminium recycling waste, recycled silicate glass from outworn fluorescence lamp recycling plant, calcined kaolinite clay supplemented with alkali activator with different silicate modulus the new type of porous material for biotechnologic processes without the need for additional equipment for pH control was researched. This controlled-release system contains an alkali activated matrix in which NaOH crystals are encased. In this study ability to release NaOH per time in water according to material composition and structure were investigated. Three alkaline activated materials AAM 7.5, 10 and 12.5, with different alkali activator content were characterized.

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Untoro, Meida Cahyo, and Fathan Rizki Hidayah. "IOT-BASED HYDROPONIC PLANT MONITORING AND CONTROL SYSTEM TO MAINTAIN PLANT FERTILITY." INTEK: Jurnal Penelitian 9, no. 1 (April 1, 2022): 33. http://dx.doi.org/10.31963/intek.v9i1.3407.

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Hydroponics is a method of cultivating plants by utilizing a small amount of land without using soil media. Hydroponic cultivation is still done conventionally in monitoring and controlling nutrients and pH of the air. Hydroponics is already with Internet of Things (IoT) technology in the cultivation process. The research aims to use IoT technology by developing control devices and monitoring hydroponic plants remotely, to make it easier for cultivators to control and monitor plant color, temperature, nutrients and the pH value of hydroponic plant water. Control and monitoring can be done through a smartphone application. The data from testing the condition of hydroponic plants obtained an average error of 1.8% for air temperature, 4.8% for water pH, 6.6% for plant color and 7% for water nutrients. Hydroponic plants with the TCS3200 sensor get a monitoring opportunity of 53.3%. Testing of tool control related to nutritional improvement has been carried out using the fuzzy Mamdani method with an increase in the probability of 88.75% for adding nutritional value and 0% for decreasing nutritional value. Tool control for improving the pH value of hydroponic plant water has been successfully carried out.

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Shimizu, Hiroshi, Eizo Sada, Suteaki Shioya, and Ken-ichi Suga. "Measurement of enzyme reaction rates using advanced pH control system: Application of repetitive PF system." Biotechnology and Bioengineering 34, no. 6 (September 1989): 794–803. http://dx.doi.org/10.1002/bit.260340609.

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