Control of Wastewater Treatment Processes Using a Fuzzy Logic Approach
The issue of pure water is currently one of the most critical concerns facing the global population. Wastewater treatment technologies are seen as one of the solutions to these water shortages. At present, despite the advancements in water treatment technology, there are still drawbacks in terms of...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-09-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/67/1/39 |
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| Summary: | The issue of pure water is currently one of the most critical concerns facing the global population. Wastewater treatment technologies are seen as one of the solutions to these water shortages. At present, despite the advancements in water treatment technology, there are still drawbacks in terms of energy consumption, the recovery ratio, and control. In order to solve the problems mentioned above, it is also very important to develop a control system method suitable for the water treatment process. In this work, the development and implementation of a fuzzy logic approach to control industrial wastewater treatment technology using an ion-exchange resin are presented. Initially, ion-exchange resin technology was developed in the laboratory as a pilot project and tested to purify wastewater at the Kungrad Soda Plant in Uzbekistan. According to technical instructions, the hardness of purified water should not exceed 3 mEq/L, the total dissolved solids (TDS) should not exceed 40 ppm, and the pH should remain below 7.5. Based on these data, the membership functions (MFs) of the parameters were formed, and the model of controlling the process through the fuzzy logic controller was developed. The developed fuzzy logic controller model was compared with the traditional controller (PID). The energy consumption ranged from 2 to 2.5 kJ/m<sup>3</sup>, and the settling time was 40 s when the process was controlled by a PID controller. By implementing the developed fuzzy logic controller in the process, it is possible to decrease the energy consumption by 1.8–2.3 kJ/m<sup>3</sup> and the settling time by 15 s. |
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| ISSN: | 2673-4591 |